To make an informed decision on the above tradeoff requires performance data for the various models . This paper addresses the issue of performance benefits from the above four consistency models . Our results are based on simulation studies done for three applications . Orchis consists of four components , data consistency models , adaptive data sampling and process protocols , consistency-driven cross-layer protocols and flexible APIs to manage the data quality , to support the goals of high data quality and energy efficiency . Firstly , a consistency model is formally defined , which not only includes temporal consistency and numerical consistency , but also considers the application-specific requirements of data and data dynamics in the sensing field . Next , an adaptive lazy energy efficient data collection protocol is proposed , which adapts the data sampling rate to the data dynamics in the sensing field and keeps lazy when the data consistency is maintained . Han and Lee proposed a path consistency algorithm , PC-4 , with O(n3a3 ) space complexity , which makes it practicable only for small problems . I present a new path consistency algorithm , PC-5 , which has an O(n3a2 ) space complexity while retaining the worst-case time complexity of PC-4 . Moreover , the new algorithm exhibits a much better average-case time complexity . This paper studies constraint satisfaction over connected row-convex ( CRC ) constraints . It shows that CRC constraints are closed under composition , intersection , and transposition , the basic operations of path-consistency algorithms . This establishes that path consistency over CRC constraints produces a minimal and decomposable network and is thus a polynomial-time decision procedure for CRC networks . We also identify unexplored areas and uninvestigated problems within the fields of database recovery and consistency preservation . We find that research on real-time recovery in distributed databases is lacking , and we also propose further investigation of how the choice of consistency preservation technique affects ( or should affect ) the design of a recovery mechanism for the system . In various medical image registration algorithms , intensity-based elastic registration has the advantage of automation of high degree , but the ambiguity in intensity correspondence in the algorithms may lead to mis-registration . The consistency registration algorithm , which used local cross correlation coefficient as the similarity metric , was proposed . The algorithm connects the forward and inverse transformations together and uses the sum of local cross correlation as similarity metric function . It allows the user to browse through a description of the available databases and to formulate queries related to data stored in them by means of a menu-based interface . By enriching technical publishing features with data consistency controls in a uniform way , ALIVE moves towards the integrated desktop concept . We prove that LC is strictly weaker than existing memory models , but is still equivalent to stronger models for the common case of parallel programs that have no data races . We also describe a new multiprocessor cache consistency protocol based on the LC memory model . We prove that this LC protocol obeys the LC memory model . The model library and diagnosis engine are the two main parts of the diagnosis system , both of which have the two-level structure that contains a consistency-based level and an abductive level . In the consistency-based level , the model and diagnosis engine of consistency-based MBD are established , which contribute to the fault detection and diagnosis candidate generation . The minimal support environment offline searching algorithm and binary particle swarm optimization with a genetic algorithm are proposed to enhance the consistency-based reasoning . Commercial data stores offer tunable consistency guarantees at transaction level where the user specifies the desired level of consistency in terms of number of participating replicas in read and write consensus . Selective data consistency model applies strict consistency to a subset of data objects . The consistency guarantees of data attributes or objects are measured using an application independent metric called consistency index ( CI ) . We introduce the Casl Consistency Checker ( CCC ) , a tool that supports consistency proofs in the algebraic specification language Casl . CCC is a faithful implementation of a previously described consistency calculus . Its system architecture combines flexibility with correctness ensured by encapsulation in a type system . The proposed algorithm simultaneously estimates global geometric transforms to align LDR images and detects moving objects and under-/over-exposed regions using a rank minimization approach . In the HDR composition step , structural consistency weighting is proposed to generate an artifact-free HDR image from an user-selected reference image . We demonstrate the robustness and effectiveness of the proposed method with real datasets . This trains the model to give consistent predictions to nearby data points , encouraging distributional smoothness in the model . Consistency regularization has been very successful for computer vision applications bachman2014learning , laine2016temporal , tarvainen2017weight . However , stochastic input alterations are more difficult to apply to discrete data like text , making consistency regularization less used for natural language processing . One solution is to add noise to the model Most of the semi - supervised image recognition approaches we compare against rely on the inputs being continuous , so they would be difficult to apply to text . More specifically , consistency regularization methods sajjadi2016regularization , laine2016temporal , miyato2017virtual rely on adding continuous noise and applying image - specific transformations like cropping to inputs , GANs salimans2016improved , wei2018improving are very difficult to train on text due to its discrete nature , and mixup zhang2017mixup , verma2018manifold requires a way of smoothly interpolating between different inputs . Approach . Our model takes the encoded content features extracted from a given input and the attribute vectors sampled from the attribute space to produce diverse outputs at test time . To handle unpaired training data , we introduce a novel cross - cycle consistency loss based on disentangled representations . Qualitative results show that our model can generate diverse and realistic images on a wide range of tasks without paired training data . Although high - quality results have been shown , the model training requires paired training data . To train with unpaired data , CycleGAN , DiscoGAN , and UNIT leverage cycle consistency to regularize the training . However , these methods perform generation conditioned solely on an input image and thus produce one single output . With the disentangled representation where the content space is shared among domains and the attribute space encodes intra - domain variations , we can perform I2I translation by combining a content representation from an arbitrary image and an attribute representation from an image of the target domain . We leverage this property and propose a cross - cycle consistency . In contrast to cycle consistency constraint in ( i.e. , ) which assumes one - to - one mapping between the two domains , the proposed cross - cycle constraint exploit the disentangled content and attribute representations for cyclic reconstruction . ( [ reference ] ) and ( [ reference ] ) ) does not guarantee that translated images preserve the content of its input images while changing only the domain - related part of the inputs . To alleviate this problem , we apply a cycle consistency loss to the generator , defined as where takes in the translated image and the original domain label as input and tries to reconstruct the original image . We adopt the L1 norm as our reconstruction loss . We first review the popular 3D morphable model that we adopt to render the 3D faces . Then we explain our method in details , in particular the novel cycle - consistency based self - supervised learning and the self - critic learning . section : 3D morphable model section : 2D assisted self - supervised learning To leverage the 2D face images with only annotation of sparse 2D landmark points offered by detector [ reference ] , we develop the following self - supervision scheme that offers three different self - supervision losses , including the 2D landmark consistency loss L 2d - con , the 3D landmark consistency loss L 3d - con and the cycle - consistency loss L cyc . We observe that in most cases , a body part belonging to a person is located inside the bounding box of the person . Based on this observation , the box consistency term is employed to encourage pixel locations inside a human bounding box B i to be associated with the i - th human detection . The box term potential at spatial location k for body part j of a human i is assigned either 0 for k / ∈ B i , or the product of the detection score , s i , and the category - level part segmentation confidence , We do not use as parameter one of the features of the instance , as done for instance in portfolios of solvers . We use as parameter the stability of values , which is a feature based on the state of the arc consistency algorithm during its execution . Parameterized local consistencies choose to enforce arc consistency or a higher level of local consistency on a value depending on whether the stability of the value is above or below a given threshold . Abstract In this paper , we extend the language we proposed in [ 11 ] to make it possible to program arc-consistency algorithms . We also propose a hybrid algorithm that integrates the interval-consistency ( IC ) and arc-consistency ( AC ) algorithms . For a constraint , the algorithm checks IC when it is non-binary and checks AC when the constraint turns into binary . The AC-3 algorithm is a basic and widely used arc consistency enforcing algorithm in Constraint Satisfaction Problems ( CSP ) . Its strength lies in that it is simple , empirically efficient and extensible . An Optimization . Arc-consistency checking has been adapted to be able to interpret over-segmented image . This adaptation lead to the arc-consistency algorithm with bilevel constraints . This can be done using constraint-based reasoning in a framework consisting of an ordinary CSP , which is only partly known , and a system of ' ' shadow CSPs ' ' that represent various forms of possibilistic knowledge . This kind of reasoning in combination with arc consistency processing can speed up search under conditions of limited communication , at the same time potentially undermining privacy . These effects are demonstrated in a simplified meeting scheduling problem where agents propose meetings consistent with their existing schedules while responding to other proposals by accepting or rejecting them . Agents store such information within ‘ views ’ of other agents . We show that this kind of possibilistic information in combination with arc consistency processing can speed up search under conditions of limited communication . This entails an important privacy/efficiency tradeoff , in that this form of reasoning requires a modicum of actual private information to be maximally effective . Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem . We aim at determining the time complexity of arc consistency testing . The input structures G and H can be supposed to be connected colored graphs , as the general problem reduces to this particular case . Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem . We aim at determining the time complexity of arc consistency testing . The input structures G and H can be supposed to be connected colored graphs , as the general problem reduces to this particular case . This new form of data structure uses explicit domain information to maintain the generalized arc consistency of table constraints . Empirical analyses demonstrate the efficiency of table constraints over the international planning competition problem and classic deep space instances in general arc consistency schema algorithms . Experimental results also prove that DSPlan and table constraints are highly promising general-purpose tools for deep space planning problems compared with other planners . As expected , the mixed scheme is superior to the 2nd-order one in terms of both accuracy and computational efficiency . For the first time , the EDAC model is assessed for the direct numerical simulation of wall-bounded turbulent flow requiring a non-uniform mesh . As a particular test case we have chosen the channel flow at the friction Reynolds numbers R e τ = 180 and 395 . Statistical data collection from a prototype in 10-nm tri-gate CMOS shows up to 122-mV VMIN reduction . Reliable pulsed latches enabled by M2/EDAC offer 12%–18 % total dynamic power savings for logic blocks in 10-nm CMOS . Based on hardware-implemented SEC-DED coding for each horizontal word , this method makes software-implemented parity coding for the vertical bit-slice , and corrects bit-flip errors of memory through software/hardware cooperation . In comparison with the hardware-only EDAC method , the proposed method can correct more bit-flip errors without increasing hardware cost . Theoretic analyses and experimental results show that , the reliability of the memory protected by the software/hardware cooperation method is higher than the reliability of memory protected by the hardware-only method to some extent . This significantly improves overall performance and alleviates pressure on the EDAC circuits . Experimental results based on the three-stage commercial CK802 processor in SMIC 40LL process present that the approach has improved the peak performance of the baseline EDAC system ( Razor-Lite + half-frequency replay ) by 8 % and reduced the energy consumption by 25 % , with less than 1.4 % area overhead . Space systems use error detection and correction ( EDAC ) schemes to protect memory contents from single event upsets ( SEUs ) . Hamming EDAC is the preferred scheme for fast , random access memories . It allows for the correction of a single bit error within a word and the detection of a double bit error . In this paper , we extend a method that augments hardware error detection and correction ( EDAC ) contextually , and show an application-based approach that takes detectable uncorrectable ( DUE ) data errors and corrects them . We applied this application-based method successfully to data errors found using common EDAC , and discuss operating system changes that will make this possible on existing systems . We show that even when there are many acceptable correction choices ( which may be seen in floating point ) , a large percentage of DUEs are corrected , and even the miscorrected data are very close to correct . Finally , using the ground and orbit test data combined with above methods , a case study of reliability assessment for RAM is given . The assessment can be combined with small sample data to quantitatively evaluate the reliability of RAM under EDAC enhanced . The assessment methodology in this paper has the characteristics of strong applicability and good portability . A 32-bit , 5-stage MIPS microprocessor data path testchip based on the proposed technique was implemented in a 65 nm CMOS technology . With the proposed onecycle EDAC technique , the silicon measurement results from 31 dies showed 24.3 % higher throughput and 8.7 % less energy consumption beyond the point of the first failure ( PoFF ) . Flash-memories are nonvolatile , shock-resistant and power-economic , but in turn have different drawbacks . A solid-state recorder for space applications should satisfy many different constraints especially because of the issues related to radiations : proper countermeasures are needed , together with EDAC and testing techniques in order to improve the dependability of the whole system . Different and quite often contrasting dimensions need to be explored during the design of a flash-memory based solid- state recorder . This paper presents a comparison of the performance of four low complexity EDAC techniques for application in Random Access Memories ( RAMs ) on-board small satellites . The performance of a newly proposed EDAC architecture is measured and compared with three different EDAC strategies , using the same FPGA technology . A statistical analysis of single-event upset ( SEU ) and multiple-bit upset ( MBU ) activity in commercial memories onboard Alsat-1 is given for a period of 8 years Keywords — Error Detection and Correction ; On-board computer ; small satellite missions It exploits timestamps for operation sequencing in distributed contexts and adopts fine-granularity dependency checking to effectively reduce the number of potential conflicts . Experimental results show that , compared with implementations using causal+ consistency model in the upper layer and Egalitarian Paxos in system layer , CC-Paxos can significantly decreases latency and increases throughput with no sacrifice on scalability . Causal consistency is one of the widely used consistency models in wide-area replicated systems due to highly scalable semantics . Partial replication is a replication mechanism that emphasizes a better network capacity utilization . While systems with these characteristics exist , they usually do not provide all these properties or do so in an inefficient manner , not taking full advantage of them . Additionally , weak consistency models , such as eventual consistency , put an excessively high burden on application programmers for writing correct applications , and hence , multiple systems have moved towards providing additional consistency guarantees such as implementing the causal ( and causal+ ) consistency models . In this thesis we approach the existing challenges in designing a causally consistent replication protocol , with a focus on the use of geo and partial data replication . Its time complexity is O(n3 d3 ) and its space complexity is O(n3 d2 ) , where n is the number of variables and d is the size of domains . We have remarked that PC-6 , though it is widely better than PC-4 ( Han & Lee 1988 ) , was not very efficient in practice , specialy for those classes of problems that require an important . space to be run . At the end of July 2018 , the journal had completed four publication cycle years , that is , publication cycle 1 ( PC-1 ) : August 2014 – July 2015 , publication cycle 2 ( PC-2 ) : August 2015 – July 2016 , publication cycle 3 ( PC-3 ) : August 2016 – July 2017 , and publication cycle 4 ( PC-4 ) : August 2017 – July 2018 . The second PC accounts for long and narrow or short and wide faces . Longer narrow orbits versus shorter wider orbits can be described by PC3 , and PC4 represents variation in the degree of ortho/prognathism with positively scoring individuals having longer , wider , and more projecting lower jaws than negatively scoring individuals . Further study will investigate the correlation between respirator fit and these PCs . The second PC accounts for long and narrow or short and wide faces . Longer narrow orbits versus shorter wider orbits can be described by PC3 , and PC4 represents variation in the degree of ortho/prognathism . Geometric Morphometrics provides a detailed and interpretable assessment of morphological variation that may be useful in assessing respirators and devising new test and certification standards . Machine learning has started to be deployed in fields such as healthcare and finance , which propelled the need for and growth of privacy-preserving machine learning ( PPML ) . We propose an actively secure four-party protocol ( 4PC ) , and a framework for PPML , showcasing its applications on four of the most widely-known machine learning algorithms -- Linear Regression , Logistic Regression , Neural Networks , and Convolutional Neural Networks . Our 4PC protocol tolerating at most one malicious corruption is practically efficient as compared to the existing works . Empirically , our protocols are on par with the best known 3PC protocol of Mohassel et al. [ CCS 2015 ] that only achieves security with selective abort , in terms of the computation time , LAN runtime , WAN runtime and communication cost . In fact , our 4PC outperforms the 3PC of Mohassel et al. significantly in terms of per-party computation and communication cost . With an extra GC , we improve the round complexity of our 4PC to four rounds . The only 4PC in our setting , given by Ishai et al. [ CRYPTO 2015 ] , involves 12 GCs . The imbalance of pattern directly affects the precision of classifier . PC 4.5 , an improved C 4.5 algorithm is proposed , which is applied in MIT dataset . The experiment indicates that PC 4.5 is effective on imbalanced datasets and the scale of the decision tree can be reduced . PBLI-E1 : Determine whether clinical evidence can be generalized to an individual patient 2 . PC-C4 : Recognize disease presentations that deviate from common patterns and that require complex decision making •Embrace zebras 1 . MK-A8 : Understand the relevant pathophysiology and basic science for uncommon or complex medical conditions 2 . The imbalance of dataset will directly affect the precision of classifier . PC4.5 , an improved C4.5 algorithm is proposed . The experiments in MIT dataset indicate that PC4.5 is effective on imbalanced dataset and the scale of the decision tree could be reduced .
To make an informed decision on the above tradeoff requires performance data for the various models . This paper addresses the issue of performance benefits from the above four consistency models . Our results are based on simulation studies done for three applications .
Orchis consists of four components , data consistency models , adaptive data sampling and process protocols , consistency-driven cross-layer protocols and flexible APIs to manage the data quality , to support the goals of high data quality and energy efficiency . Firstly , a consistency model is formally defined , which not only includes temporal consistency and numerical consistency , but also considers the application-specific requirements of data and data dynamics in the sensing field . Next , an adaptive lazy energy efficient data collection protocol is proposed , which adapts the data sampling rate to the data dynamics in the sensing field and keeps lazy when the data consistency is maintained .
Han and Lee proposed a path consistency algorithm , PC-4 , with O(n3a3 ) space complexity , which makes it practicable only for small problems . I present a new path consistency algorithm , PC-5 , which has an O(n3a2 ) space complexity while retaining the worst-case time complexity of PC-4 . Moreover , the new algorithm exhibits a much better average-case time complexity .
This paper studies constraint satisfaction over connected row-convex ( CRC ) constraints . It shows that CRC constraints are closed under composition , intersection , and transposition , the basic operations of path-consistency algorithms . This establishes that path consistency over CRC constraints produces a minimal and decomposable network and is thus a polynomial-time decision procedure for CRC networks .
We also identify unexplored areas and uninvestigated problems within the fields of database recovery and consistency preservation . We find that research on real-time recovery in distributed databases is lacking , and we also propose further investigation of how the choice of consistency preservation technique affects ( or should affect ) the design of a recovery mechanism for the system .
In various medical image registration algorithms , intensity-based elastic registration has the advantage of automation of high degree , but the ambiguity in intensity correspondence in the algorithms may lead to mis-registration . The consistency registration algorithm , which used local cross correlation coefficient as the similarity metric , was proposed . The algorithm connects the forward and inverse transformations together and uses the sum of local cross correlation as similarity metric function .
It allows the user to browse through a description of the available databases and to formulate queries related to data stored in them by means of a menu-based interface . By enriching technical publishing features with data consistency controls in a uniform way , ALIVE moves towards the integrated desktop concept .
We prove that LC is strictly weaker than existing memory models , but is still equivalent to stronger models for the common case of parallel programs that have no data races . We also describe a new multiprocessor cache consistency protocol based on the LC memory model . We prove that this LC protocol obeys the LC memory model .
The model library and diagnosis engine are the two main parts of the diagnosis system , both of which have the two-level structure that contains a consistency-based level and an abductive level . In the consistency-based level , the model and diagnosis engine of consistency-based MBD are established , which contribute to the fault detection and diagnosis candidate generation . The minimal support environment offline searching algorithm and binary particle swarm optimization with a genetic algorithm are proposed to enhance the consistency-based reasoning .
Commercial data stores offer tunable consistency guarantees at transaction level where the user specifies the desired level of consistency in terms of number of participating replicas in read and write consensus . Selective data consistency model applies strict consistency to a subset of data objects . The consistency guarantees of data attributes or objects are measured using an application independent metric called consistency index ( CI ) .
We introduce the Casl Consistency Checker ( CCC ) , a tool that supports consistency proofs in the algebraic specification language Casl . CCC is a faithful implementation of a previously described consistency calculus . Its system architecture combines flexibility with correctness ensured by encapsulation in a type system .
The proposed algorithm simultaneously estimates global geometric transforms to align LDR images and detects moving objects and under-/over-exposed regions using a rank minimization approach . In the HDR composition step , structural consistency weighting is proposed to generate an artifact-free HDR image from an user-selected reference image . We demonstrate the robustness and effectiveness of the proposed method with real datasets .
This trains the model to give consistent predictions to nearby data points , encouraging distributional smoothness in the model . Consistency regularization has been very successful for computer vision applications bachman2014learning , laine2016temporal , tarvainen2017weight . However , stochastic input alterations are more difficult to apply to discrete data like text , making consistency regularization less used for natural language processing . One solution is to add noise to the model
Most of the semi - supervised image recognition approaches we compare against rely on the inputs being continuous , so they would be difficult to apply to text . More specifically , consistency regularization methods sajjadi2016regularization , laine2016temporal , miyato2017virtual rely on adding continuous noise and applying image - specific transformations like cropping to inputs , GANs salimans2016improved , wei2018improving are very difficult to train on text due to its discrete nature , and mixup zhang2017mixup , verma2018manifold requires a way of smoothly interpolating between different inputs . Approach .
Our model takes the encoded content features extracted from a given input and the attribute vectors sampled from the attribute space to produce diverse outputs at test time . To handle unpaired training data , we introduce a novel cross - cycle consistency loss based on disentangled representations . Qualitative results show that our model can generate diverse and realistic images on a wide range of tasks without paired training data .
Although high - quality results have been shown , the model training requires paired training data . To train with unpaired data , CycleGAN , DiscoGAN , and UNIT leverage cycle consistency to regularize the training . However , these methods perform generation conditioned solely on an input image and thus produce one single output .
With the disentangled representation where the content space is shared among domains and the attribute space encodes intra - domain variations , we can perform I2I translation by combining a content representation from an arbitrary image and an attribute representation from an image of the target domain . We leverage this property and propose a cross - cycle consistency . In contrast to cycle consistency constraint in ( i.e. , ) which assumes one - to - one mapping between the two domains , the proposed cross - cycle constraint exploit the disentangled content and attribute representations for cyclic reconstruction .
( [ reference ] ) and ( [ reference ] ) ) does not guarantee that translated images preserve the content of its input images while changing only the domain - related part of the inputs . To alleviate this problem , we apply a cycle consistency loss to the generator , defined as where takes in the translated image and the original domain label as input and tries to reconstruct the original image . We adopt the L1 norm as our reconstruction loss .
We first review the popular 3D morphable model that we adopt to render the 3D faces . Then we explain our method in details , in particular the novel cycle - consistency based self - supervised learning and the self - critic learning . section : 3D morphable model
section : 2D assisted self - supervised learning To leverage the 2D face images with only annotation of sparse 2D landmark points offered by detector [ reference ] , we develop the following self - supervision scheme that offers three different self - supervision losses , including the 2D landmark consistency loss L 2d - con , the 3D landmark consistency loss L 3d - con and the cycle - consistency loss L cyc .
We observe that in most cases , a body part belonging to a person is located inside the bounding box of the person . Based on this observation , the box consistency term is employed to encourage pixel locations inside a human bounding box B i to be associated with the i - th human detection . The box term potential at spatial location k for body part j of a human i is assigned either 0 for k / ∈ B i , or the product of the detection score , s i , and the category - level part segmentation confidence ,
We do not use as parameter one of the features of the instance , as done for instance in portfolios of solvers . We use as parameter the stability of values , which is a feature based on the state of the arc consistency algorithm during its execution . Parameterized local consistencies choose to enforce arc consistency or a higher level of local consistency on a value depending on whether the stability of the value is above or below a given threshold .
Abstract In this paper , we extend the language we proposed in [ 11 ] to make it possible to program arc-consistency algorithms . We also propose a hybrid algorithm that integrates the interval-consistency ( IC ) and arc-consistency ( AC ) algorithms . For a constraint , the algorithm checks IC when it is non-binary and checks AC when the constraint turns into binary .
The AC-3 algorithm is a basic and widely used arc consistency enforcing algorithm in Constraint Satisfaction Problems ( CSP ) . Its strength lies in that it is simple , empirically efficient and extensible .
An Optimization . Arc-consistency checking has been adapted to be able to interpret over-segmented image . This adaptation lead to the arc-consistency algorithm with bilevel constraints .
This can be done using constraint-based reasoning in a framework consisting of an ordinary CSP , which is only partly known , and a system of ' ' shadow CSPs ' ' that represent various forms of possibilistic knowledge . This kind of reasoning in combination with arc consistency processing can speed up search under conditions of limited communication , at the same time potentially undermining privacy . These effects are demonstrated in a simplified meeting scheduling problem where agents propose meetings consistent with their existing schedules while responding to other proposals by accepting or rejecting them .
Agents store such information within ‘ views ’ of other agents . We show that this kind of possibilistic information in combination with arc consistency processing can speed up search under conditions of limited communication . This entails an important privacy/efficiency tradeoff , in that this form of reasoning requires a modicum of actual private information to be maximally effective .
Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem . We aim at determining the time complexity of arc consistency testing . The input structures G and H can be supposed to be connected colored graphs , as the general problem reduces to this particular case .
Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem . We aim at determining the time complexity of arc consistency testing . The input structures G and H can be supposed to be connected colored graphs , as the general problem reduces to this particular case .
This new form of data structure uses explicit domain information to maintain the generalized arc consistency of table constraints . Empirical analyses demonstrate the efficiency of table constraints over the international planning competition problem and classic deep space instances in general arc consistency schema algorithms . Experimental results also prove that DSPlan and table constraints are highly promising general-purpose tools for deep space planning problems compared with other planners .
As expected , the mixed scheme is superior to the 2nd-order one in terms of both accuracy and computational efficiency . For the first time , the EDAC model is assessed for the direct numerical simulation of wall-bounded turbulent flow requiring a non-uniform mesh . As a particular test case we have chosen the channel flow at the friction Reynolds numbers R e τ = 180 and 395 .
Statistical data collection from a prototype in 10-nm tri-gate CMOS shows up to 122-mV VMIN reduction . Reliable pulsed latches enabled by M2/EDAC offer 12%–18 % total dynamic power savings for logic blocks in 10-nm CMOS .
Based on hardware-implemented SEC-DED coding for each horizontal word , this method makes software-implemented parity coding for the vertical bit-slice , and corrects bit-flip errors of memory through software/hardware cooperation . In comparison with the hardware-only EDAC method , the proposed method can correct more bit-flip errors without increasing hardware cost . Theoretic analyses and experimental results show that , the reliability of the memory protected by the software/hardware cooperation method is higher than the reliability of memory protected by the hardware-only method to some extent .
This significantly improves overall performance and alleviates pressure on the EDAC circuits . Experimental results based on the three-stage commercial CK802 processor in SMIC 40LL process present that the approach has improved the peak performance of the baseline EDAC system ( Razor-Lite + half-frequency replay ) by 8 % and reduced the energy consumption by 25 % , with less than 1.4 % area overhead .
Space systems use error detection and correction ( EDAC ) schemes to protect memory contents from single event upsets ( SEUs ) . Hamming EDAC is the preferred scheme for fast , random access memories . It allows for the correction of a single bit error within a word and the detection of a double bit error .
In this paper , we extend a method that augments hardware error detection and correction ( EDAC ) contextually , and show an application-based approach that takes detectable uncorrectable ( DUE ) data errors and corrects them . We applied this application-based method successfully to data errors found using common EDAC , and discuss operating system changes that will make this possible on existing systems . We show that even when there are many acceptable correction choices ( which may be seen in floating point ) , a large percentage of DUEs are corrected , and even the miscorrected data are very close to correct .
Finally , using the ground and orbit test data combined with above methods , a case study of reliability assessment for RAM is given . The assessment can be combined with small sample data to quantitatively evaluate the reliability of RAM under EDAC enhanced . The assessment methodology in this paper has the characteristics of strong applicability and good portability .
A 32-bit , 5-stage MIPS microprocessor data path testchip based on the proposed technique was implemented in a 65 nm CMOS technology . With the proposed onecycle EDAC technique , the silicon measurement results from 31 dies showed 24.3 % higher throughput and 8.7 % less energy consumption beyond the point of the first failure ( PoFF ) .
Flash-memories are nonvolatile , shock-resistant and power-economic , but in turn have different drawbacks . A solid-state recorder for space applications should satisfy many different constraints especially because of the issues related to radiations : proper countermeasures are needed , together with EDAC and testing techniques in order to improve the dependability of the whole system . Different and quite often contrasting dimensions need to be explored during the design of a flash-memory based solid- state recorder .
This paper presents a comparison of the performance of four low complexity EDAC techniques for application in Random Access Memories ( RAMs ) on-board small satellites . The performance of a newly proposed EDAC architecture is measured and compared with three different EDAC strategies , using the same FPGA technology . A statistical analysis of single-event upset ( SEU ) and multiple-bit upset ( MBU ) activity in commercial memories onboard Alsat-1 is given for a period of 8 years Keywords — Error Detection and Correction ; On-board computer ; small satellite missions
It exploits timestamps for operation sequencing in distributed contexts and adopts fine-granularity dependency checking to effectively reduce the number of potential conflicts . Experimental results show that , compared with implementations using causal+ consistency model in the upper layer and Egalitarian Paxos in system layer , CC-Paxos can significantly decreases latency and increases throughput with no sacrifice on scalability .
Causal consistency is one of the widely used consistency models in wide-area replicated systems due to highly scalable semantics . Partial replication is a replication mechanism that emphasizes a better network capacity utilization .
While systems with these characteristics exist , they usually do not provide all these properties or do so in an inefficient manner , not taking full advantage of them . Additionally , weak consistency models , such as eventual consistency , put an excessively high burden on application programmers for writing correct applications , and hence , multiple systems have moved towards providing additional consistency guarantees such as implementing the causal ( and causal+ ) consistency models . In this thesis we approach the existing challenges in designing a causally consistent replication protocol , with a focus on the use of geo and partial data replication .
Its time complexity is O(n3 d3 ) and its space complexity is O(n3 d2 ) , where n is the number of variables and d is the size of domains . We have remarked that PC-6 , though it is widely better than PC-4 ( Han & Lee 1988 ) , was not very efficient in practice , specialy for those classes of problems that require an important . space to be run .
At the end of July 2018 , the journal had completed four publication cycle years , that is , publication cycle 1 ( PC-1 ) : August 2014 – July 2015 , publication cycle 2 ( PC-2 ) : August 2015 – July 2016 , publication cycle 3 ( PC-3 ) : August 2016 – July 2017 , and publication cycle 4 ( PC-4 ) : August 2017 – July 2018 .
The second PC accounts for long and narrow or short and wide faces . Longer narrow orbits versus shorter wider orbits can be described by PC3 , and PC4 represents variation in the degree of ortho/prognathism with positively scoring individuals having longer , wider , and more projecting lower jaws than negatively scoring individuals . Further study will investigate the correlation between respirator fit and these PCs .
The second PC accounts for long and narrow or short and wide faces . Longer narrow orbits versus shorter wider orbits can be described by PC3 , and PC4 represents variation in the degree of ortho/prognathism . Geometric Morphometrics provides a detailed and interpretable assessment of morphological variation that may be useful in assessing respirators and devising new test and certification standards .
Machine learning has started to be deployed in fields such as healthcare and finance , which propelled the need for and growth of privacy-preserving machine learning ( PPML ) . We propose an actively secure four-party protocol ( 4PC ) , and a framework for PPML , showcasing its applications on four of the most widely-known machine learning algorithms -- Linear Regression , Logistic Regression , Neural Networks , and Convolutional Neural Networks . Our 4PC protocol tolerating at most one malicious corruption is practically efficient as compared to the existing works .
Empirically , our protocols are on par with the best known 3PC protocol of Mohassel et al. [ CCS 2015 ] that only achieves security with selective abort , in terms of the computation time , LAN runtime , WAN runtime and communication cost . In fact , our 4PC outperforms the 3PC of Mohassel et al. significantly in terms of per-party computation and communication cost . With an extra GC , we improve the round complexity of our 4PC to four rounds . The only 4PC in our setting , given by Ishai et al. [ CRYPTO 2015 ] , involves 12 GCs .
The imbalance of pattern directly affects the precision of classifier . PC 4.5 , an improved C 4.5 algorithm is proposed , which is applied in MIT dataset . The experiment indicates that PC 4.5 is effective on imbalanced datasets and the scale of the decision tree can be reduced .
PBLI-E1 : Determine whether clinical evidence can be generalized to an individual patient 2 . PC-C4 : Recognize disease presentations that deviate from common patterns and that require complex decision making •Embrace zebras 1 . MK-A8 : Understand the relevant pathophysiology and basic science for uncommon or complex medical conditions 2 .
The imbalance of dataset will directly affect the precision of classifier . PC4.5 , an improved C4.5 algorithm is proposed . The experiments in MIT dataset indicate that PC4.5 is effective on imbalanced dataset and the scale of the decision tree could be reduced .
Performance evaluation of memory consistency models for shared-memory multiprocessors Data Quality Management in Wireless Sensor Networks Path Consistency Revisited Constraint Satisfaction over Connected Row Convex Constraints On recovery and consistency preservation in distributed real-time database systems Intensity-based consistent elastic registration algorithm ALIVE: A Distributed Live-Link Documentation System Location Consistency-A New Memory Model and Cache Consistency Protocol A Model-Based Diagnosis System for a Traction Power Supply System Tunable consistency guarantees of selective data consistency model CCC - The Casl Consistency Checker High dynamic range imaging by a rank-1 constraint Semi-Supervised Sequence Modeling with Cross-View Training Diverse Image-to-Image Translation via Disentangled Representations StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation Joint 3D Face Reconstruction and Dense Face Alignment from A Single Image with 2D-Assisted Self-Supervised Learning Holistic, Instance-Level Human Parsing Adaptive Parameterized Consistency A Hybrid Algorithm for Compiling Equality Constraints and its Implementation Making AC-3 an Optimal Algorithm Arc-Consistency Checking with Bilevel Constraints: An Optimization Constraint-based reasoning and privacy/efficiency tradeoffs in multi-agent problem solving Possibilistic Reasoning and Privacy/Efficiency Tradeoffs in Multi-agent Systems On the speed of constraint propagation and the time complexity of arc consistency testing On the Speed of Constraint Propagation and the Time Complexity of Arc Consistency Testing A Constraint-Programmed Planner for Deep Space Exploration Problems With Table Constraints Application of the Entropically Damped Artificial Compressibility model to direct numerical simulation of turbulent channel flow Min-Delay Margin/Error Detection and Correction for Flip-Flops and Pulsed Latches in 10-nm CMOS A Software/Hardware Cooperation EDAC Method against Bit-Flips of Memory Eliminating Timing Errors Through Collaborative Design to Maximize the Throughput Simplified Birthday Statistics and Hamming EDAC Improving Application Resilience by Extending Error Correction with Contextual Information Single Event Upset Reliability Assessment for RAM Based on Maximum Entropy Principle and Bootstrap Low-overhead, one-cycle timing-error detection and correction technique for flip-flop based pipelines Flash-memories in Space Applications: Trends and Challenges Performance Comparison of Real Time EDAC Systems for Applications On-Board Small Satellites CC-Paxos: Integrating Consistency and Reliability in Wide-Area Storage Systems Performance of Approximate Causal Consistency for Partially Replicated Systems A novel causally consistent replication protocol with partial geo-replication Path-Consistency: When Space Misses Time Four years of development as a gathering place for international researchers and readers in STEM education Facial Shape Variation of U.S. Respirator Users Shape Analysis of 3D Head Scan Data for U.S. Respirator Users Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning Fast Secure Computation for Small Population over the Internet PC 4.5: Improved C 4.5 algorithm applied in imbalanced dataset Addendum: Reducing Diagnostic Error by Using Educational Milestones to Organize Curricula and Assessment Using an improved C4.5 for imbalanced dataset of intrusion
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ASPLOS WADT ICIP EMNLP ECCV 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition ArXiv BMVC CP IJCAI GbRPR MICAI MFCS ESSCIRC FTXS@SC ICPADS ARMS-CC@PODC AAAI/IAAI, Vol. 1 HCI (11) ACM Conference on Computer and Communications Security PST
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