wanyu/IteraTeR_v2 huggingface dataset:
Original:  These services necessitate secure system logging to aid audit and forensic investigations , particularly if devices bring harm to users . Logs should be tamper-resistant  , both during executionand in storage, while being retrievable by remote verifiers in a secure fashion .
Revised:  These services necessitate secure system logging to aid audit and forensic investigations , particularly if devices bring harm to users . Logs should be tamper-resistant , and when retrieved by a trusted remote verifier .
Edit intent: clarity
Original:  In recent years, Trusted Execution Environments (TEEs) have emerged as the go-to root of trust on mobile and embedded devices for hardware-enforced isolated execution of sensitive applications.
Revised:  In recent years, Trusted Execution Environments (TEEs) have emerged as the go-to root of trust on constrained devices for isolated execution of sensitive applications.
Edit intent: clarity
Original:  Existing TEE-based logging systems, however, focus largely on protecting server-side logs and offer little protection to logs from mobile and embedded source devices.
Revised:  Existing TEE-based logging systems, however, focus largely on protecting server-side logs and offer little protection to constrained source devices.
Edit intent: clarity
Original:  In this paper, we introduce EmLog , a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides strong protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Revised:  In this paper, we introduce EmLog -- a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides strong protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Edit intent: fluency
Original:  In this paper, we introduce EmLog , a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides strong protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Revised:  In this paper, we introduce EmLog , a tamper-resistant logging system for constrained devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides strong protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Edit intent: clarity
Original:  In this paper, we introduce EmLog , a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides strong protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Revised:  In this paper, we introduce EmLog , a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE . EmLog provides strong protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Edit intent: coherence
Original:  In this paper, we introduce EmLog , a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides strong protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Revised:  In this paper, we introduce EmLog , a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Edit intent: clarity
Original:  In this paper, we introduce EmLog , a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides strong protection against complex software adversaries and offers several further security properties over past schemes , such as public verifiability of log origin.
Revised:  In this paper, we introduce EmLog , a tamper-resistant logging system with trust assurances for these devices using the GlobalPlatform TEE and ARM TrustZone . EmLog provides strong protection against complex software adversaries and offers several additional security properties over past schemes , such as public verifiability of log origin.
Edit intent: fluency
Original:  This is evaluated across a variety of log datasets using a GlobalPlatform-compliant TEE on an off-the-shelf ARM development board  .
Revised:  This is evaluated across three log datasets using a GlobalPlatform-compliant TEE on an off-the-shelf ARM development board .
Edit intent: clarity
Original:  On average, EmLog has a throughput of 135 logs/second, runs with low run-time memory overhead (1MB heap and stack) and yields five-times persistent storage overhead for providing tamper-resistance .
Revised:  On average, EmLog runs with low run-time memory overhead (1MB heap and stack) and yields five-times persistent storage overhead for providing tamper-resistance .
Edit intent: clarity
Original:  On average, EmLog has a throughput of 135 logs/second, runs with low run-time memory overhead (1MB heap and stack) and yields five-times persistent storage overhead for providing tamper-resistance .
Revised:  On average, EmLog has a throughput of 135 logs/second, runs with low run-time memory overhead (1MB heap and stack) and yields five-times persistent storage overhead versus unprotected logs .
Edit intent: clarity
Original: The goal of this paper is to increase our understanding of the fundamental performance limits of urban vehicle networks by exploiting the self-similarity and hierarchical organization of modern cities.
Revised: This paper studies the fundamental communication properties of urban vehicle networks by exploiting the self-similarity and hierarchical organization of modern cities.
Edit intent: clarity
Original:  We use an innovative model called "hyperfractal" that captures the self-similarity of the topology and vehicle locations while avoiding the extremes of regularity and randomness.
Revised:  We use an innovative model called "hyperfractal" that captures the self-similarities of both the traffic and vehicle locations while avoiding the extremes of regularity and randomness.
Edit intent: clarity
Original:  We use an innovative model called "hyperfractal" that captures the self-similarity of the topology and vehicle locations while avoiding the extremes of regularity and randomness.
Revised:  We use an innovative model called "hyperfractal" that captures the self-similarity of the topology and vehicle locations but avoids the extremes of regularity and randomness.
Edit intent: coherence
Original:  We use analytical tools to derive matching theoretical upper and lower bounds for the information propagation speed of a broadcast in an urban delay tolerant network which is disconnected at all time, i.e., where end-to-end multihop paths may not exist (requiring a store-carry-and-forward routing model).
Revised:  We use analytical tools to derive theoretical upper and lower bounds for the information propagation speed of a broadcast in an urban delay tolerant network which is disconnected at all time, i.e., where end-to-end multihop paths may not exist (requiring a store-carry-and-forward routing model).
Edit intent: clarity
Original:  We use analytical tools to derive matching theoretical upper and lower bounds for the information propagation speed of a broadcast in an urban delay tolerant network which is disconnected at all time, i.e., where end-to-end multihop paths may not exist (requiring a store-carry-and-forward routing model).
Revised:  We use analytical tools to derive matching theoretical upper and lower bounds for the information propagation speed in an urban delay tolerant network which is disconnected at all time, i.e., where end-to-end multihop paths may not exist (requiring a store-carry-and-forward routing model).
Edit intent: clarity
Original:  We use analytical tools to derive matching theoretical upper and lower bounds for the information propagation speed of a broadcast in an urban delay tolerant network which is disconnected at all time, i.e., where end-to-end multihop paths may not exist (requiring a store-carry-and-forward routing model).
Revised:  We use analytical tools to derive matching theoretical upper and lower bounds for the information propagation speed of a broadcast in an urban delay tolerant network (i.e., a network that is disconnected at all time, i.e., where end-to-end multihop paths may not exist (requiring a store-carry-and-forward routing model).
Edit intent: clarity
Original:  We use analytical tools to derive matching theoretical upper and lower bounds for the information propagation speed of a broadcast in an urban delay tolerant network which is disconnected at all time, i.e., where end-to-end multihop paths may not exist (requiring a store-carry-and-forward routing model).
Revised:  We use analytical tools to derive matching theoretical upper and lower bounds for the information propagation speed of a broadcast in an urban delay tolerant network which is disconnected at all time, and thus uses a store-carry-and-forward routing model).
Edit intent: coherence
Original:  We prove that the average broadcast time in a hyperfractal setup is in \Theta(n^{1-\delta \delta depends on the precise hyperfractal dimension.
Revised:  We prove that the average broadcast time behaves as n^{1-\delta \delta depends on the precise hyperfractal dimension.
Edit intent: clarity
Original:  We prove that the average broadcast time in a hyperfractal setup is in \Theta(n^{1-\delta \delta depends on the precise hyperfractal dimension.
Revised:  We prove that the average broadcast time in a hyperfractal setup is in \Theta(n^{1-\delta \delta depends on the precise fractal dimension.
Edit intent: fluency
Original:  Furthermore, we show that the performance is due in part to an interesting self-similar phenomenon, that we denote as {\em information teleportation} , that arises as a consequence of the topology and allows an acceleration of the broadcast time.
Revised:  Furthermore, we show that the broadcast speedup is due in part to an interesting self-similar phenomenon, that we denote as {\em information teleportation} , that arises as a consequence of the topology and allows an acceleration of the broadcast time.
Edit intent: clarity
Original:  Furthermore, we show that the performance is due in part to an interesting self-similar phenomenon, that we denote as {\em information teleportation} , that arises as a consequence of the topology and allows an acceleration of the broadcast time.
Revised:  Furthermore, we show that the performance is due in part to an interesting self-similar phenomenon, that we denote as {\em information teleportation} . This phenomenon arises as a consequence of the topology and allows an acceleration of the broadcast time.
Edit intent: clarity
Original:   Motivated by this, we study the problem of obtaining persistent homology based summaries of time-dependent metric data.
Revised:  Motivated by this, we study the problem of obtaining persistent homology based summaries of time-dependent data.
Edit intent: clarity
Original:  This includes key techniques such as exploratory fitness landscape analysis and response surface methodology .
Revised:  This includes key techniques such as exploratory fitness landscape analysis and sensititvity analysis .
Edit intent: clarity
Original: We study the vulnerability of synthetic as well as real-world networks in  center-based attacks.
Revised: We study the vulnerability of synthetic as well as real-world networks in these center-based attacks.
Edit intent: clarity
Original:  We empirically compare the proposed heuristics between them and against existing (local) process mining techniques in terms of coverage, precision , and complexity of the produced sets of LPMs.
Revised:  We empirically compare the proposed heuristics between them and against existing (local) process mining techniques in terms of coverage, redundancy , and complexity of the produced sets of LPMs.
Edit intent: clarity
Original:  We comment on experimental results obtained by an implementation based on the C++ libraries LinBox, Eigen and NTL.
Revised:  We comment on experimental results obtained by an implementation based on the C++ libraries Eigen, LinBox and NTL.
Edit intent: fluency
Original: Method for increasing precision of feedforward networks is presented.
Revised: A method to increase the precision of feedforward networks is presented.
Edit intent: fluency
Original:  Forward pass calculates not only  values of the output layer of the network but also their derivatives.
Revised:  Forward pass calculates not only the values of the output layer of the network but also their derivatives.
Edit intent: fluency
Original:  Forward pass calculates not only  values of the output layer of the network but also their derivatives.
Revised:  Forward pass calculates not only values of the output layer of a network but also their derivatives.
Edit intent: fluency
Original:  Deviations of those derivatives from the target ones are used in an extended cost function and then backward pass calculates  gradient of the extended cost with respect to weights, which is then can be used by any weights update algorithm.
Revised:  The deviations of those derivatives from the target ones are used in an extended cost function and then backward pass calculates gradient of the extended cost with respect to weights, which is then can be used by any weights update algorithm.
Edit intent: fluency
Original:  Deviations of those derivatives from the target ones are used in an extended cost function and then backward pass calculates  gradient of the extended cost with respect to weights, which is then can be used by any weights update algorithm.
Revised:  Deviations of those derivatives from the target ones are used in an extended cost function and then backward pass calculates the gradient of the extended cost with respect to weights, which is then can be used by any weights update algorithm.
Edit intent: fluency
Original:  Deviations of those derivatives from the target ones are used in an extended cost function and then backward pass calculates  gradient of the extended cost with respect to weights, which is then can be used by any weights update algorithm.
Revised:  Deviations of those derivatives from the target ones are used in an extended cost function and then backward pass calculates gradient of the extended cost with respect to weights, which can then be used by any weights update algorithm.
Edit intent: fluency
Original:  Despite a substantial increase of arithmetic operations per pattern (if compared to the conventional training), the extended cost allows to obtain 140--1000 times more accurate approximation for simple cases if the total number of operations is equal.
Revised:  Despite a substantial increase in arithmetic operations per pattern (if compared to the conventional training), the extended cost allows to obtain 140--1000 times more accurate approximation for simple cases if the total number of operations is equal.
Edit intent: fluency
Original:  Unlike training a network to match some target mapping, which requires an explicit use of  target derivatives in an extended cost function, the cost function for solving a differential equation is based on the deviation of the equation's residual from zero and thus can be extended by differentiating the equation itself, which does not require any prior knowledge.
Revised:  Unlike training a network to match some target mapping, which requires an explicit use of the target derivatives in an extended cost function, the cost function for solving a differential equation is based on the deviation of the equation's residual from zero and thus can be extended by differentiating the equation itself, which does not require any prior knowledge.
Edit intent: fluency
Original:  Unlike training a network to match some target mapping, which requires an explicit use of  target derivatives in an extended cost function, the cost function for solving a differential equation is based on the deviation of the equation's residual from zero and thus can be extended by differentiating the equation itself, which does not require any prior knowledge.
Revised:  Unlike training a network to match some target mapping, which requires an explicit use of target derivatives in the extended cost function, the cost function for solving a differential equation is based on the deviation of the equation's residual from zero and thus can be extended by differentiating the equation itself, which does not require any prior knowledge.
Edit intent: fluency
Original:  GPU-efficient algorithm for calculating gradient of an extended cost function is proposed.
Revised:  GPU-efficient algorithm for calculating the gradient of the extended cost function is proposed.
Edit intent: fluency
Original:  In this letter we propose a simple SIS epidemic model on an adaptive network with time-delayed rewiring, and show that oscillatory solutions are now present in a wide region of the parameter space.
Revised:  In this paper we propose a simple SIS epidemic model on an adaptive network with time-delayed rewiring, and show that oscillatory solutions are now present in a wide region of the parameter space.
Edit intent: clarity
Original: Place cells in the hippocampus are active when an animal visits a certain locations (referred to as place fields ) within an environment and remain silent otherwise . Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that exhibit a hexagonally symmetric periodic pattern .
Revised: Place cells in the hippocampus are active when an animal visits a certain location (referred to as place fields ) within an environment and remain silent otherwise . Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that exhibit a hexagonally symmetric periodic pattern .
Edit intent: fluency
Original: Place cells in the hippocampus are active when an animal visits a certain locations (referred to as place fields ) within an environment and remain silent otherwise . Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that exhibit a hexagonally symmetric periodic pattern .
Revised: Place cells in the hippocampus are active when an animal visits a certain locations (referred to as a place field ) within an environment and remain silent otherwise . Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that exhibit a hexagonally symmetric periodic pattern .
Edit intent: fluency
Original: Place cells in the hippocampus are active when an animal visits a certain locations (referred to as place fields ) within an environment and remain silent otherwise . Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that exhibit a hexagonally symmetric periodic pattern .
Revised: Place cells in the hippocampus are active when an animal visits a certain locations (referred to as place fields ) within an environment . Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that exhibit a hexagonally symmetric periodic pattern .
Edit intent: coherence
Original: Place cells in the hippocampus are active when an animal visits a certain locations (referred to as place fields ) within an environment and remain silent otherwise . Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that exhibit a hexagonally symmetric periodic pattern .
Revised: Place cells in the hippocampus are active when an animal visits a certain locations (referred to as place fields ) within an environment and remain silent otherwise . Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that form a periodic and hexagonal tiling of the environment .
Edit intent: clarity
Original:  An ensemble of codes , for a given set of parameters, is generated by selecting grid and place cell population and tuning curve parameters.
Revised:  An ensemble of codes is generated by selecting grid and place cell population and tuning curve parameters.
Edit intent: clarity
Original:  An ensemble of codes , for a given set of parameters, is generated by selecting grid and place cell population and tuning curve parameters.
Revised:  An ensemble of codes , for a given set of parameters, is generated by varying grid and place cell population and tuning curve parameters.
Edit intent: clarity
Original:  An ensemble of codes , for a given set of parameters, is generated by selecting grid and place cell population and tuning curve parameters.
Revised:  An ensemble of codes , for a given set of parameters, is generated by selecting grid and place cell population parameters.
Edit intent: clarity
Original:  For each  ensemble, codewords are generated by stimulating a network with a discrete set of locations.
Revised:  For each code in this ensemble, codewords are generated by stimulating a network with a discrete set of locations.
Edit intent: clarity
Original:  These observations are revisited by measuring the performances of biologically realizable algorithms (e.g. neural bit-flipping) implemented by a network of place and grid cell populations, as well as interneurons , which perform de-noising operations.
Revised:  These relationships are revisited by measuring the performances of biologically realizable algorithms (e.g. neural bit-flipping) implemented by a network of place and grid cell populations, as well as interneurons , which perform de-noising operations.
Edit intent: clarity
Original:  These observations are revisited by measuring the performances of biologically realizable algorithms (e.g. neural bit-flipping) implemented by a network of place and grid cell populations, as well as interneurons , which perform de-noising operations.
Revised:  These observations are revisited by measuring the performances of biologically realizable algorithms implemented by networks of place and grid cell populations, as well as interneurons , which perform de-noising operations.
Edit intent: clarity
Original:  These observations are revisited by measuring the performances of biologically realizable algorithms (e.g. neural bit-flipping) implemented by a network of place and grid cell populations, as well as interneurons , which perform de-noising operations.
Revised:  These observations are revisited by measuring the performances of biologically realizable algorithms (e.g. neural bit-flipping) implemented by a network of place and grid cell populations, as well as constraint neurons , which perform de-noising operations.
Edit intent: clarity
Original:  Recent work has shown that a deep learning system using the complex numbers can be deeper for a set parameter budget compared to its real-valued counterpart.
Revised:  Recent work has shown that a deep learning system using the complex numbers can be deeper for a fixed parameter budget compared to its real-valued counterpart.
Edit intent: clarity
Original:  These pieces are tested  by end-to-end training on the CIFAR-10 and CIFAR-100 data sets to show the improved convergence to a real-valued network .
Revised:  These pieces are tested in a classification model by end-to-end training on the CIFAR-10 and CIFAR-100 data sets to show the improved convergence to a real-valued network .
Edit intent: clarity