To enhance information security during transmission over public channels,images are frequently employed for binary data hiding.Nonetheless,data are vulnerable to distortion due to Joint Photographic Experts Group(JPEG...To enhance information security during transmission over public channels,images are frequently employed for binary data hiding.Nonetheless,data are vulnerable to distortion due to Joint Photographic Experts Group(JPEG)compression,leading to challenges in recovering the original binary data.Addressing this issue,this paper introduces a pioneering method for binary data hiding that leverages a combined spatial and channel attention Transformer,termed SCFformer,to withstand JPEG compression.This method employs a novel discrete cosine transform(DCT)quantization truncation mechanism during the hiding phase to bolster the stego image’s resistance to JPEG compression,using spatial and channel attention to conceal information in less perceptible areas,thereby enhancing the model’s resistance to steganalysis.In the extraction phase,the DCT quantization minimizes secret image loss during compression,facilitating easier information retrieval.The incorporation of scalable modules adds flexibility,allowing for variable-capacity data hiding.Experimental findings validate the high security,large capacity,and high flexibility of our scheme,alongside a marked improvement in binary data recovery post-JPEG compression,underscoring our method’s leading-edge performance.展开更多
For analyzing correlated binary data with high-dimensional covariates,we,in this paper,propose a two-stage shrinkage approach.First,we construct a weighted least-squares(WLS) type function using a special weighting sc...For analyzing correlated binary data with high-dimensional covariates,we,in this paper,propose a two-stage shrinkage approach.First,we construct a weighted least-squares(WLS) type function using a special weighting scheme on the non-conservative vector field of the generalized estimating equations(GEE) model.Second,we define a penalized WLS in the spirit of the adaptive LASSO for simultaneous variable selection and parameter estimation.The proposed procedure enjoys the oracle properties in high-dimensional framework where the number of parameters grows to infinity with the number of clusters.Moreover,we prove the consistency of the sandwich formula of the covariance matrix even when the working correlation matrix is misspecified.For the selection of tuning parameter,we develop a consistent penalized quadratic form(PQF) function criterion.The performance of the proposed method is assessed through a comparison with the existing methods and through an application to a crossover trial in a pain relief study.展开更多
In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of inform...In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of information technology.A matrix decoding method is proposed in this paper.The method is a universal data reconstruction scheme for erasure codes over binary fields.Besides a pre-judgment that whether errors can be recovered,the method can rebuild sectors of loss data on a fault-tolerant storage system constructed by erasure codes for disk errors.Data reconstruction process of the new method has simple and clear steps,so it is beneficial for implementation of computer codes.And more,it can be applied to other non-binary fields easily,so it is expected that the method has an extensive application in the future.展开更多
In this paper a critical assessment and optimization of the phase diagrams and thermodynamic properties of the PrCl_3-MCl(M=Li,Na)and PrCl_3-MCl_2(M=Mg,Ca,Sr,Ba) binary systems have been per- formed.The assessed and o...In this paper a critical assessment and optimization of the phase diagrams and thermodynamic properties of the PrCl_3-MCl(M=Li,Na)and PrCl_3-MCl_2(M=Mg,Ca,Sr,Ba) binary systems have been per- formed.The assessed and optimized binary phase diagrams and thermodynamic data with self consistency are a better basis for constructing multicomponent phase diagrams.展开更多
Photometric observations of AH Cnc, a W UMa-type system in the open cluster M67, were car- fled out by using the 50BIN telescope. About 100h of time-series/3- and V-band data were taken, based on which eight new times...Photometric observations of AH Cnc, a W UMa-type system in the open cluster M67, were car- fled out by using the 50BIN telescope. About 100h of time-series/3- and V-band data were taken, based on which eight new times of light minima were determined. By applying the Wilson-Devinney method, the light curves were modeled and a revised photometric solution of the binary system was derived. We con- firmed that AH Cnc is a deep contact （f = 51%）, low mass-ratio （q - 0.156） system. Adopting the distance modulus derived from study of the host cluster, we have re-calculated the physical parameters of the binary system, namely the masses and radii. The masses and radii of the two components were estimated to be respectively 1.188（4-0.061） Me, 1.332（4-0.063） RQ for the primary component and 0.185（4-0.032） Me, 0.592（4-0.051） Re for the secondary. By adding the newly derived minimum timings to all the available data, the period variations of AH Cnc were studied. This shows that the orbital period of the binary is con- tinuously increasing at a rate of dp/dt = 4.29 x 10-10 d yr-1. In addition to the long-term period increase, a cyclic variation with a period of 35.26 yr was determined, which could be attributed to an unresolved tertiary component of the system.展开更多
Emergence of drug resistant bacteria is one of the serious problems in today’s public health. However, the relationship between genomic mutation of bacteria and the phenotypic difference of them is still unclear. In ...Emergence of drug resistant bacteria is one of the serious problems in today’s public health. However, the relationship between genomic mutation of bacteria and the phenotypic difference of them is still unclear. In this paper, based on the mutation information in whole genome sequences of 96 MRSA strains, two kinds of phenotypes (pathogenicity and drug resistance) were learnt and predicted by machine learning algorithms. As a result of effective feature selection by cross entropy based sparse logistic regression, these phenotypes could be predicted in sufficiently high accuracy (100% and 97.87%, respectively) with less than 10 features. It means that we could develop a novel rapid test method in the future for checking MRSA phenotypes.展开更多
This paper presents a new approach to identify and estimate the dispersion parameters for bivariate, trivariate and multivariate correlated binary data, not only with scalar value but also with matrix values. For this...This paper presents a new approach to identify and estimate the dispersion parameters for bivariate, trivariate and multivariate correlated binary data, not only with scalar value but also with matrix values. For this direction, we present some recent studies indicating the impact of over-dispersion on the univariate data analysis and comparing a new approach with these studies. Following the property of McCullagh and Nelder [1] for identifying dispersion parameter in univariate case, we extended this property to analyze the correlated binary data in higher cases. Finally, we used these estimates to modify the correlated binary data, to decrease its over-dispersion, using the Hunua Ranges data as an ecology problem.展开更多
For name-based routing/switching in NDN, the key challenges are to manage large-scale forwarding Tables, to lookup long names of variable lengths, and to deal with frequent updates. Hashing associated with proper leng...For name-based routing/switching in NDN, the key challenges are to manage large-scale forwarding Tables, to lookup long names of variable lengths, and to deal with frequent updates. Hashing associated with proper length-detecting is a straightforward yet efficient solution. Binary search strategy can reduce the number of required hash detecting in the worst case. However, to assure the searching path correct in such a schema, either backtrack searching or redundantly storing some prefixes is required, leading to performance or memory issues as a result. In this paper, we make a deep study on the binary search, and propose a novel mechanism to ensure correct searching path without neither additional backtrack costs nor redundant memory consumptions. Along any binary search path, a bloom filter is employed at each branching point to verify whether a said prefix is present, instead of storing that prefix here. By this means, we can gain significantly optimization on memory efficiency, at the cost of bloom checking before each detecting. Our evaluation experiments on both real-world and randomly synthesized data sets demonstrate our superiorities clearly展开更多
A low mass X-ray binary （LMXB） contains either a neutron star or a black hole accreting materials from its low mass companion star. It is one of the primary astrophysical sources for studying stellar-mass compact ob...A low mass X-ray binary （LMXB） contains either a neutron star or a black hole accreting materials from its low mass companion star. It is one of the primary astrophysical sources for studying stellar-mass compact objects and accreting phe- nomena. As with other binary systems, the most important parameter of an LMXB is the orbital period, which allows us to learn about the nature of the binary system and constrain the properties of the system＇s components, including the compact ob- ject. As a result, measuring the orbital periods of LMXBs is essential for investigating these systems even though fewer than half of them have known orbital periods. This article introduces the different methods for measuring the orbital periods in the X-ray band and reviews their application to various types of LMXBs, such as eclipsing and dipping sources, as well as pulsar LMXBs.展开更多
Unlike traditional clustering analysis,the biclustering algorithm works simultaneously on two dimensions of samples(row)and variables(column).In recent years,biclustering methods have been developed rapidly and widely...Unlike traditional clustering analysis,the biclustering algorithm works simultaneously on two dimensions of samples(row)and variables(column).In recent years,biclustering methods have been developed rapidly and widely applied in biological data analysis,text clustering,recommendation system and other fields.The traditional clustering algorithms cannot be well adapted to process high-dimensional data and/or large-scale data.At present,most of the biclustering algorithms are designed for the differentially expressed big biological data.However,there is little discussion on binary data clustering mining such as miRNA-targeted gene data.Here,we propose a novel biclustering method for miRNA-targeted gene data based on graph autoencoder named as GAEBic.GAEBic applies graph autoencoder to capture the similarity of sample sets or variable sets,and takes a new irregular clustering strategy to mine biclusters with excellent generalization.Based on the miRNA-targeted gene data of soybean,we benchmark several different types of the biclustering algorithm,and find that GAEBic performs better than Bimax,Bibit and the Spectral Biclustering algorithm in terms of target gene enrichment.This biclustering method achieves comparable performance on the high throughput miRNA data of soybean and it can also be used for other species.展开更多
The lower confidence limits for response probabilities based on binary response data under the logistic response model are considered by saddlepoint approach.The high order approximation to the conditional distributio...The lower confidence limits for response probabilities based on binary response data under the logistic response model are considered by saddlepoint approach.The high order approximation to the conditional distribution of a statistic for an interested parameter and then the lower confidence limits of response probabilities are derived.A simulation comparing these lower confidence limits with those obtained from the asymptotic normality is conducted.The proposed approximation is applied to two real data sets.Numerical results show that the saddlepoint approximations are much more accurate than the asymptotic normality approximations,especially for the cases of small or moderate sample sizes.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.U1904123,62172280,and U20B2051)the Key Scientific Research Projects of Colleges and Universities in Henan Province,China(No.23A520006)the Henan Provincial Science and Technology Research Project,China(No.222102210199)。
文摘To enhance information security during transmission over public channels,images are frequently employed for binary data hiding.Nonetheless,data are vulnerable to distortion due to Joint Photographic Experts Group(JPEG)compression,leading to challenges in recovering the original binary data.Addressing this issue,this paper introduces a pioneering method for binary data hiding that leverages a combined spatial and channel attention Transformer,termed SCFformer,to withstand JPEG compression.This method employs a novel discrete cosine transform(DCT)quantization truncation mechanism during the hiding phase to bolster the stego image’s resistance to JPEG compression,using spatial and channel attention to conceal information in less perceptible areas,thereby enhancing the model’s resistance to steganalysis.In the extraction phase,the DCT quantization minimizes secret image loss during compression,facilitating easier information retrieval.The incorporation of scalable modules adds flexibility,allowing for variable-capacity data hiding.Experimental findings validate the high security,large capacity,and high flexibility of our scheme,alongside a marked improvement in binary data recovery post-JPEG compression,underscoring our method’s leading-edge performance.
基金supported by National Natural Science Foundation of China(Grant No.11201306)the Innovation Program of Shanghai Municipal Education Commission(Grant No.13YZ065)+2 种基金the Fundamental Research Project of Shanghai Normal University(Grant No.SK201207)the scholarship under the State Scholarship Fund by the China Scholarship Council in 2011the Research Grant Council of Hong Kong, Hong Kong,China(Grant No.#HKBU2028/10P)
文摘For analyzing correlated binary data with high-dimensional covariates,we,in this paper,propose a two-stage shrinkage approach.First,we construct a weighted least-squares(WLS) type function using a special weighting scheme on the non-conservative vector field of the generalized estimating equations(GEE) model.Second,we define a penalized WLS in the spirit of the adaptive LASSO for simultaneous variable selection and parameter estimation.The proposed procedure enjoys the oracle properties in high-dimensional framework where the number of parameters grows to infinity with the number of clusters.Moreover,we prove the consistency of the sandwich formula of the covariance matrix even when the working correlation matrix is misspecified.For the selection of tuning parameter,we develop a consistent penalized quadratic form(PQF) function criterion.The performance of the proposed method is assessed through a comparison with the existing methods and through an application to a crossover trial in a pain relief study.
基金supported by the National Natural Science Foundation of China under Grant No.61501064Sichuan Provincial Science and Technology Project under Grant No.2016GZ0122
文摘In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of information technology.A matrix decoding method is proposed in this paper.The method is a universal data reconstruction scheme for erasure codes over binary fields.Besides a pre-judgment that whether errors can be recovered,the method can rebuild sectors of loss data on a fault-tolerant storage system constructed by erasure codes for disk errors.Data reconstruction process of the new method has simple and clear steps,so it is beneficial for implementation of computer codes.And more,it can be applied to other non-binary fields easily,so it is expected that the method has an extensive application in the future.
文摘In this paper a critical assessment and optimization of the phase diagrams and thermodynamic properties of the PrCl_3-MCl(M=Li,Na)and PrCl_3-MCl_2(M=Mg,Ca,Sr,Ba) binary systems have been per- formed.The assessed and optimized binary phase diagrams and thermodynamic data with self consistency are a better basis for constructing multicomponent phase diagrams.
基金supported by the National Natural Science Foundation of China(Nos. U1131121,11303021,U1231202,11473037 and 11373073)
文摘Photometric observations of AH Cnc, a W UMa-type system in the open cluster M67, were car- fled out by using the 50BIN telescope. About 100h of time-series/3- and V-band data were taken, based on which eight new times of light minima were determined. By applying the Wilson-Devinney method, the light curves were modeled and a revised photometric solution of the binary system was derived. We con- firmed that AH Cnc is a deep contact （f = 51%）, low mass-ratio （q - 0.156） system. Adopting the distance modulus derived from study of the host cluster, we have re-calculated the physical parameters of the binary system, namely the masses and radii. The masses and radii of the two components were estimated to be respectively 1.188（4-0.061） Me, 1.332（4-0.063） RQ for the primary component and 0.185（4-0.032） Me, 0.592（4-0.051） Re for the secondary. By adding the newly derived minimum timings to all the available data, the period variations of AH Cnc were studied. This shows that the orbital period of the binary is con- tinuously increasing at a rate of dp/dt = 4.29 x 10-10 d yr-1. In addition to the long-term period increase, a cyclic variation with a period of 35.26 yr was determined, which could be attributed to an unresolved tertiary component of the system.
文摘Emergence of drug resistant bacteria is one of the serious problems in today’s public health. However, the relationship between genomic mutation of bacteria and the phenotypic difference of them is still unclear. In this paper, based on the mutation information in whole genome sequences of 96 MRSA strains, two kinds of phenotypes (pathogenicity and drug resistance) were learnt and predicted by machine learning algorithms. As a result of effective feature selection by cross entropy based sparse logistic regression, these phenotypes could be predicted in sufficiently high accuracy (100% and 97.87%, respectively) with less than 10 features. It means that we could develop a novel rapid test method in the future for checking MRSA phenotypes.
文摘This paper presents a new approach to identify and estimate the dispersion parameters for bivariate, trivariate and multivariate correlated binary data, not only with scalar value but also with matrix values. For this direction, we present some recent studies indicating the impact of over-dispersion on the univariate data analysis and comparing a new approach with these studies. Following the property of McCullagh and Nelder [1] for identifying dispersion parameter in univariate case, we extended this property to analyze the correlated binary data in higher cases. Finally, we used these estimates to modify the correlated binary data, to decrease its over-dispersion, using the Hunua Ranges data as an ecology problem.
基金supported by the National Natural Science Foundation of China (Grant No. 61472130 and 61702174)the China Postdoctoral Science Foundation funded project
文摘For name-based routing/switching in NDN, the key challenges are to manage large-scale forwarding Tables, to lookup long names of variable lengths, and to deal with frequent updates. Hashing associated with proper length-detecting is a straightforward yet efficient solution. Binary search strategy can reduce the number of required hash detecting in the worst case. However, to assure the searching path correct in such a schema, either backtrack searching or redundantly storing some prefixes is required, leading to performance or memory issues as a result. In this paper, we make a deep study on the binary search, and propose a novel mechanism to ensure correct searching path without neither additional backtrack costs nor redundant memory consumptions. Along any binary search path, a bloom filter is employed at each branching point to verify whether a said prefix is present, instead of storing that prefix here. By this means, we can gain significantly optimization on memory efficiency, at the cost of bloom checking before each detecting. Our evaluation experiments on both real-world and randomly synthesized data sets demonstrate our superiorities clearly
基金partially supported by the Taiwan Ministry of Science and Technology grant NSC 102-2112-M-008-020-MY3
文摘A low mass X-ray binary （LMXB） contains either a neutron star or a black hole accreting materials from its low mass companion star. It is one of the primary astrophysical sources for studying stellar-mass compact objects and accreting phe- nomena. As with other binary systems, the most important parameter of an LMXB is the orbital period, which allows us to learn about the nature of the binary system and constrain the properties of the system＇s components, including the compact ob- ject. As a result, measuring the orbital periods of LMXBs is essential for investigating these systems even though fewer than half of them have known orbital periods. This article introduces the different methods for measuring the orbital periods in the X-ray band and reviews their application to various types of LMXBs, such as eclipsing and dipping sources, as well as pulsar LMXBs.
基金This work was supported by the National Natural Science Foundation of China under Grant No.62072210the Project of the Development and Reform Commission of Jilin Province of China under Grant No.2019C053-6.
文摘Unlike traditional clustering analysis,the biclustering algorithm works simultaneously on two dimensions of samples(row)and variables(column).In recent years,biclustering methods have been developed rapidly and widely applied in biological data analysis,text clustering,recommendation system and other fields.The traditional clustering algorithms cannot be well adapted to process high-dimensional data and/or large-scale data.At present,most of the biclustering algorithms are designed for the differentially expressed big biological data.However,there is little discussion on binary data clustering mining such as miRNA-targeted gene data.Here,we propose a novel biclustering method for miRNA-targeted gene data based on graph autoencoder named as GAEBic.GAEBic applies graph autoencoder to capture the similarity of sample sets or variable sets,and takes a new irregular clustering strategy to mine biclusters with excellent generalization.Based on the miRNA-targeted gene data of soybean,we benchmark several different types of the biclustering algorithm,and find that GAEBic performs better than Bimax,Bibit and the Spectral Biclustering algorithm in terms of target gene enrichment.This biclustering method achieves comparable performance on the high throughput miRNA data of soybean and it can also be used for other species.
文摘The lower confidence limits for response probabilities based on binary response data under the logistic response model are considered by saddlepoint approach.The high order approximation to the conditional distribution of a statistic for an interested parameter and then the lower confidence limits of response probabilities are derived.A simulation comparing these lower confidence limits with those obtained from the asymptotic normality is conducted.The proposed approximation is applied to two real data sets.Numerical results show that the saddlepoint approximations are much more accurate than the asymptotic normality approximations,especially for the cases of small or moderate sample sizes.
