Ferromagnetic semiconductor Ga_(1–x)Mn_(x)As_(1–y)P_(y) thin films go through a metal–insulator transition at low temperature where electrical conduction becomes driven by hopping of charge carriers.In this regime,...Ferromagnetic semiconductor Ga_(1–x)Mn_(x)As_(1–y)P_(y) thin films go through a metal–insulator transition at low temperature where electrical conduction becomes driven by hopping of charge carriers.In this regime,we report a colossal negative magnetoresistance(CNMR)coexisting with a saturated magnetic moment,unlike in the traditional magnetic semiconductor Ga_(1–x)Mn_(x)As.By analyzing the temperature dependence of the resistivity at fixed magnetic field,we demonstrate that the CNMR can be consistently described by the field dependence of the localization length,which relates to a field dependent mobility edge.This dependence is likely due to the random environment of Mn atoms in Ga_(1-x)Mn_(x)As_(1-y)P_(y) which causes a random spatial distribution of the mobility that is suppressed by an increasing magnetic field.展开更多
Energy level statistics of a system consisting of six particles interacting by delta force in a two- model coupled with a deformed core is studied in particle-rotor model. For single- shell and two- shell the exact ...Energy level statistics of a system consisting of six particles interacting by delta force in a two- model coupled with a deformed core is studied in particle-rotor model. For single- shell and two- shell the exact energies for our statistical analysis are obtained from a full diagonalization of the Hamiltonian, while in two- case the configuration truncation is used. The nearest-neighbor distribution of energy levels and spectral rigidity are studied as the function of spin. The results of single- shell are compared with those in two- case. It is showed that the system becomes more regular when single- space is replaced by two- shell although the basis size of the configuration space is unchanged. The degree of chaoticity of the system, however, changes slightly when configuration space is enlarged by extending single- shell to two- shell .展开更多
We study a nonintegrable discrete nonlinear SchriSdinger （dNLS） equation with the term of nonlinear nearest-neighbor interaction occurred in nonlinear optical waveguide arrays. By using discrete Fourier transformati...We study a nonintegrable discrete nonlinear SchriSdinger （dNLS） equation with the term of nonlinear nearest-neighbor interaction occurred in nonlinear optical waveguide arrays. By using discrete Fourier transformation, we obtain numerical approximations of stationary and travelling solitary wave solutions of the nonintegrable dNLS equation. The analysis of stability of stationary solitary waves is performed. It is shown that the nonlinear nearest-neighbor interaction term has great influence on the form of solitary wave. The shape of solitary wave is important in the electric field propagating. If we neglect the nonlinear nearest-neighbor interaction term, much important information in the electric field propagating may be missed. Our numerical simulation also demonstrates the difference of chaos phenomenon between the nonintegrable dNLS equation with nonlinear nearest-neighbor interaction and another nonintegrable dNLS equation without the term.展开更多
The chaotic properties for six particles interacting by a monopole pairing force in a two-j shell model coupled with a deformed core are studied in the frame of particle-rotor model. The nearest-neighbor distribution ...The chaotic properties for six particles interacting by a monopole pairing force in a two-j shell model coupled with a deformed core are studied in the frame of particle-rotor model. The nearest-neighbor distribution of energy levels and spectral rigidity in the two-j shell are compared with those in the single-j case. The results show that the system is more regular in the two-j model than that in the single-j case.展开更多
Using a statistical method which is based on random matrix theory, the results for the nearest-neighbor energy spacing distributions E(S) obtained from experimental as well as from computational data have been selecte...Using a statistical method which is based on random matrix theory, the results for the nearest-neighbor energy spacing distributions E(S) obtained from experimental as well as from computational data have been selected for review study. The obtained results confirm that the energy spacing correlation between secondary charged particles depends upon the charged particles multiplicity and central collisions are also associated with charged particles multiplicity.展开更多
The operating temperature of a proton exchange membrane fuel cell stack is a very important control parameter. It should be controlled within a specific range, however, most of existing PEMFC mathematical models are t...The operating temperature of a proton exchange membrane fuel cell stack is a very important control parameter. It should be controlled within a specific range, however, most of existing PEMFC mathematical models are too complicated to be effectively applied to on-line control. In this paper, input-output data and operating experiences will be used to establish PEMFC stack model and operating temperature control system. An adaptive learning algorithm and a nearest-neighbor clustering algorithm are applied to regulate the parameters and fuzzy rules so that the model and the control system are able to obtain higher accuracy. In the end, the simulation and the experimental results are presented and compared with traditional PID and fuzzy control algorithms.展开更多
Software defect prediction （SDP） is an active research field in software engineering to identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively allocated to defect-prone modules. A...Software defect prediction （SDP） is an active research field in software engineering to identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively allocated to defect-prone modules. Although SDP requires sufficient local data within a company, there are cases where local data are not available, e.g., pilot projects. Companies without local data can employ cross-project defect prediction （CPDP） using external data to build classifiers. The major challenge of CPDP is different distributions between training and test data. To tackle this, instances of source data similar to target data are selected to build classifiers. Software datasets have a class imbalance problem meaning the ratio of defective class to clean class is far low. It usually lowers the performance of classifiers. We propose a Hybrid Instance Selection Using Nearest-Neighbor （HISNN） method that performs a hybrid classification selectively learning local knowledge （via k-nearest neighbor） and global knowledge （via na/ve Bayes）. Instances having strong local knowledge are identified via nearest-neighbors with the same class label. Previous studies showed low PD （probability of detection） or high PF （probability of false alarm） which is impractical to overall performance as well as high PD and low PF. use. The experimental results show that HISNN produces high overall performance as well as high PD and low PF.展开更多
Marginal Fisher analysis （MFA） is a repre- sentative margin-based learning algorithm for face recognition. A major problem in MFA is how to select appropriate parameters, k1 and k2, to construct the respective intri...Marginal Fisher analysis （MFA） is a repre- sentative margin-based learning algorithm for face recognition. A major problem in MFA is how to select appropriate parameters, k1 and k2, to construct the respective intrinsic and penalty graphs. In this paper, we propose a novel method called nearest-neighbor （NN） classifier motivated marginal discriminant projections （NN-MDP）. Motivated by the NN classifier, NN-MDP seeks a few projection vectors to prevent data samples from being wrongly categorized. Like MFA, NN-MDP can characterize the compactness and separability of samples simultaneously. Moreover, in contrast to MFA, NN-MDP can actively construct the intrinsic graph and penalty graph without unknown parameters. Experimental results on the 0RL, Yale, and FERET face databases show that NN-MDP not only avoids the intractability, and high expense of neighborhood parameter selection, but is also more applicable to face recognition with NN classifier than other methods.展开更多
Recently, the issue of privacy preserving loca- tion queries has attracted much research. However, there are few works focusing on the tradeoff between location privacy preservation and location query information coll...Recently, the issue of privacy preserving loca- tion queries has attracted much research. However, there are few works focusing on the tradeoff between location privacy preservation and location query information collection. To tackle this kind of tradeoff, we propose the privacy persevering location query （PLQ）, an efficient privacy pre-serving location query processing framework. This frame- work can enable the location-based query without revealing user location information. The framework can also facilitate location-based service providers to collect some information about the location based query, which is useful in practice. PLQ consists of three key components, namely, the location anonymizer at the client side, the privacy query processor at the server side, and an additional trusted third party connect- ing the client and server. The location anonymizer blurs the user location into a cloaked area based on a map-hierarchy. The map-hierarchy contains accurate regions that are parti- tioned according to real landforms. The privacy query pro- cessor deals with the requested nearest-neighbor （NN） loca- tion based query. A new convex hull of polygon （CHP） algo- rithm is proposed for nearest-neighbor queries using a poly- gon cloaked area. The experimental results show that our al- gorithms can efficiently process location based queries.展开更多
We consider the nearest-neighbor model on the finite tree T with generator L. We obtain a twosided estimate of the spectral gap by factor 2. We also identify explicitly the Lipschitzian norm of the operator(-L)^(-1) i...We consider the nearest-neighbor model on the finite tree T with generator L. We obtain a twosided estimate of the spectral gap by factor 2. We also identify explicitly the Lipschitzian norm of the operator(-L)^(-1) in propriate functional space. This leads to the identification of the best constant in the generalized Cheeger isoperimetric inequality on the tree, and to transportation-information inequalities.展开更多
Aims Measures of plot-to-plot phylogenetic dissimilarity and beta diversity are providing a powerful tool for understanding the complex ecolog-ical and evolutionary mechanisms that drive community assembly.Methods Her...Aims Measures of plot-to-plot phylogenetic dissimilarity and beta diversity are providing a powerful tool for understanding the complex ecolog-ical and evolutionary mechanisms that drive community assembly.Methods Here,we review the properties of some previously published dis-similarity measures that are based on minimum or average phylo-genetic dissimilarity between species in different plots.Important Findings We first show that some of these measures violate the basic condi-tion that for two identical plots the measures take the value zero.They also violate the condition that the dissimilarity between two identical plots should always be lower than that between two differ-ent plots.Such erratic behavior renders these measures unsuitable for measuring plot-to-plot phylogenetic dissimilarity.We next pro-pose a new measure that satisfies these conditions,thus providing a more reasonable way for measuring phylogenetic dissimilarity.展开更多
基金This work was supported by the National Science Foundation Grant No.DMR 1905277.
文摘Ferromagnetic semiconductor Ga_(1–x)Mn_(x)As_(1–y)P_(y) thin films go through a metal–insulator transition at low temperature where electrical conduction becomes driven by hopping of charge carriers.In this regime,we report a colossal negative magnetoresistance(CNMR)coexisting with a saturated magnetic moment,unlike in the traditional magnetic semiconductor Ga_(1–x)Mn_(x)As.By analyzing the temperature dependence of the resistivity at fixed magnetic field,we demonstrate that the CNMR can be consistently described by the field dependence of the localization length,which relates to a field dependent mobility edge.This dependence is likely due to the random environment of Mn atoms in Ga_(1-x)Mn_(x)As_(1-y)P_(y) which causes a random spatial distribution of the mobility that is suppressed by an increasing magnetic field.
文摘Energy level statistics of a system consisting of six particles interacting by delta force in a two- model coupled with a deformed core is studied in particle-rotor model. For single- shell and two- shell the exact energies for our statistical analysis are obtained from a full diagonalization of the Hamiltonian, while in two- case the configuration truncation is used. The nearest-neighbor distribution of energy levels and spectral rigidity are studied as the function of spin. The results of single- shell are compared with those in two- case. It is showed that the system becomes more regular when single- space is replaced by two- shell although the basis size of the configuration space is unchanged. The degree of chaoticity of the system, however, changes slightly when configuration space is enlarged by extending single- shell to two- shell .
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11671255 and 11701510)the Ministry of Economy and Competitiveness of Spain(Grant No.MTM2016-80276-P(AEI/FEDER,EU))the China Postdoctoral Science Foundation(Grant No.2017M621964)
文摘We study a nonintegrable discrete nonlinear SchriSdinger （dNLS） equation with the term of nonlinear nearest-neighbor interaction occurred in nonlinear optical waveguide arrays. By using discrete Fourier transformation, we obtain numerical approximations of stationary and travelling solitary wave solutions of the nonintegrable dNLS equation. The analysis of stability of stationary solitary waves is performed. It is shown that the nonlinear nearest-neighbor interaction term has great influence on the form of solitary wave. The shape of solitary wave is important in the electric field propagating. If we neglect the nonlinear nearest-neighbor interaction term, much important information in the electric field propagating may be missed. Our numerical simulation also demonstrates the difference of chaos phenomenon between the nonintegrable dNLS equation with nonlinear nearest-neighbor interaction and another nonintegrable dNLS equation without the term.
文摘The chaotic properties for six particles interacting by a monopole pairing force in a two-j shell model coupled with a deformed core are studied in the frame of particle-rotor model. The nearest-neighbor distribution of energy levels and spectral rigidity in the two-j shell are compared with those in the single-j case. The results show that the system is more regular in the two-j model than that in the single-j case.
文摘Using a statistical method which is based on random matrix theory, the results for the nearest-neighbor energy spacing distributions E(S) obtained from experimental as well as from computational data have been selected for review study. The obtained results confirm that the energy spacing correlation between secondary charged particles depends upon the charged particles multiplicity and central collisions are also associated with charged particles multiplicity.
文摘The operating temperature of a proton exchange membrane fuel cell stack is a very important control parameter. It should be controlled within a specific range, however, most of existing PEMFC mathematical models are too complicated to be effectively applied to on-line control. In this paper, input-output data and operating experiences will be used to establish PEMFC stack model and operating temperature control system. An adaptive learning algorithm and a nearest-neighbor clustering algorithm are applied to regulate the parameters and fuzzy rules so that the model and the control system are able to obtain higher accuracy. In the end, the simulation and the experimental results are presented and compared with traditional PID and fuzzy control algorithms.
文摘Software defect prediction （SDP） is an active research field in software engineering to identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively allocated to defect-prone modules. Although SDP requires sufficient local data within a company, there are cases where local data are not available, e.g., pilot projects. Companies without local data can employ cross-project defect prediction （CPDP） using external data to build classifiers. The major challenge of CPDP is different distributions between training and test data. To tackle this, instances of source data similar to target data are selected to build classifiers. Software datasets have a class imbalance problem meaning the ratio of defective class to clean class is far low. It usually lowers the performance of classifiers. We propose a Hybrid Instance Selection Using Nearest-Neighbor （HISNN） method that performs a hybrid classification selectively learning local knowledge （via k-nearest neighbor） and global knowledge （via na/ve Bayes）. Instances having strong local knowledge are identified via nearest-neighbors with the same class label. Previous studies showed low PD （probability of detection） or high PF （probability of false alarm） which is impractical to overall performance as well as high PD and low PF. use. The experimental results show that HISNN produces high overall performance as well as high PD and low PF.
文摘Marginal Fisher analysis （MFA） is a repre- sentative margin-based learning algorithm for face recognition. A major problem in MFA is how to select appropriate parameters, k1 and k2, to construct the respective intrinsic and penalty graphs. In this paper, we propose a novel method called nearest-neighbor （NN） classifier motivated marginal discriminant projections （NN-MDP）. Motivated by the NN classifier, NN-MDP seeks a few projection vectors to prevent data samples from being wrongly categorized. Like MFA, NN-MDP can characterize the compactness and separability of samples simultaneously. Moreover, in contrast to MFA, NN-MDP can actively construct the intrinsic graph and penalty graph without unknown parameters. Experimental results on the 0RL, Yale, and FERET face databases show that NN-MDP not only avoids the intractability, and high expense of neighborhood parameter selection, but is also more applicable to face recognition with NN classifier than other methods.
文摘Recently, the issue of privacy preserving loca- tion queries has attracted much research. However, there are few works focusing on the tradeoff between location privacy preservation and location query information collection. To tackle this kind of tradeoff, we propose the privacy persevering location query （PLQ）, an efficient privacy pre-serving location query processing framework. This frame- work can enable the location-based query without revealing user location information. The framework can also facilitate location-based service providers to collect some information about the location based query, which is useful in practice. PLQ consists of three key components, namely, the location anonymizer at the client side, the privacy query processor at the server side, and an additional trusted third party connect- ing the client and server. The location anonymizer blurs the user location into a cloaked area based on a map-hierarchy. The map-hierarchy contains accurate regions that are parti- tioned according to real landforms. The privacy query pro- cessor deals with the requested nearest-neighbor （NN） loca- tion based query. A new convex hull of polygon （CHP） algo- rithm is proposed for nearest-neighbor queries using a poly- gon cloaked area. The experimental results show that our al- gorithms can efficiently process location based queries.
基金National Natural Science Foundation of China (Grant Nos. 11271294, 11101040, 11431014 and 11371283)Beijing Youth Excellent Talents Program (Grant No. 0264)+1 种基金National Creative Group under Beijing Normal University 985 Projectsthe Fundamental Research Funds for the Central Universities and le Project ANR EVOL
文摘We consider the nearest-neighbor model on the finite tree T with generator L. We obtain a twosided estimate of the spectral gap by factor 2. We also identify explicitly the Lipschitzian norm of the operator(-L)^(-1) in propriate functional space. This leads to the identification of the best constant in the generalized Cheeger isoperimetric inequality on the tree, and to transportation-information inequalities.
文摘Aims Measures of plot-to-plot phylogenetic dissimilarity and beta diversity are providing a powerful tool for understanding the complex ecolog-ical and evolutionary mechanisms that drive community assembly.Methods Here,we review the properties of some previously published dis-similarity measures that are based on minimum or average phylo-genetic dissimilarity between species in different plots.Important Findings We first show that some of these measures violate the basic condi-tion that for two identical plots the measures take the value zero.They also violate the condition that the dissimilarity between two identical plots should always be lower than that between two differ-ent plots.Such erratic behavior renders these measures unsuitable for measuring plot-to-plot phylogenetic dissimilarity.We next pro-pose a new measure that satisfies these conditions,thus providing a more reasonable way for measuring phylogenetic dissimilarity.
