432 research outputs found
Improved Feature Weight Algorithm and Its Application to Text Classification
Text preprocessing is one of the key problems in pattern recognition and plays an important role in the process of text classification. Text preprocessing has two pivotal steps: feature selection and feature weighting. The preprocessing results can directly affect the classifiersâ accuracy and performance. Therefore, choosing the appropriate algorithm for feature selection and feature weighting to preprocess the document can greatly improve the performance of classifiers. According to the Gini Index theory, this paper proposes an Improved Gini Index algorithm. This algorithm constructs a new feature selection and feature weighting function. The experimental results show that this algorithm can improve the classifiersâ performance effectively. At the same time, this algorithm is applied to a sensitive information identification system and has achieved a good result. The algorithmâs precision and recall are higher than those of traditional ones. It can identify sensitive information on the Internet effectively
Multidifferential study of identified charged hadron distributions in -tagged jets in proton-proton collisions at 13 TeV
Jet fragmentation functions are measured for the first time in proton-proton
collisions for charged pions, kaons, and protons within jets recoiling against
a boson. The charged-hadron distributions are studied longitudinally and
transversely to the jet direction for jets with transverse momentum 20 GeV and in the pseudorapidity range . The
data sample was collected with the LHCb experiment at a center-of-mass energy
of 13 TeV, corresponding to an integrated luminosity of 1.64 fb. Triple
differential distributions as a function of the hadron longitudinal momentum
fraction, hadron transverse momentum, and jet transverse momentum are also
measured for the first time. This helps constrain transverse-momentum-dependent
fragmentation functions. Differences in the shapes and magnitudes of the
measured distributions for the different hadron species provide insights into
the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any
supplementary material and additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb
public pages
Study of the decay
The decay is studied
in proton-proton collisions at a center-of-mass energy of TeV
using data corresponding to an integrated luminosity of 5
collected by the LHCb experiment. In the system, the
state observed at the BaBar and Belle experiments is
resolved into two narrower states, and ,
whose masses and widths are measured to be where the first uncertainties are statistical and the second
systematic. The results are consistent with a previous LHCb measurement using a
prompt sample. Evidence of a new
state is found with a local significance of , whose mass and width
are measured to be and , respectively. In addition, evidence of a new decay mode
is found with a significance of
. The relative branching fraction of with respect to the
decay is measured to be , where the first
uncertainty is statistical, the second systematic and the third originates from
the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb
public pages
Measurement of the ratios of branching fractions and
The ratios of branching fractions
and are measured, assuming isospin symmetry, using a
sample of proton-proton collision data corresponding to 3.0 fb of
integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The
tau lepton is identified in the decay mode
. The measured values are
and
, where the first uncertainty is
statistical and the second is systematic. The correlation between these
measurements is . Results are consistent with the current average
of these quantities and are at a combined 1.9 standard deviations from the
predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb
public pages
A new method of dynamic network security analysis based on dynamic uncertain causality graph
Abstract In the context of cloud computing, network attackers usually exhibit complex, dynamic, and diverse behavior characteristics. Existing research methods, such as Bayesian attack graphs, lack evidence correlation and real-time reflection of the network attack events, and high computational complexity for attack analysis. To solve these problems, this study proposes a Dynamic Uncertain Causal Attack Graph (DUCAG) model and a Causal Chain-based Risk Probability Calculation (CCRP) algorithm. The DUCAG model is constructed to represent the uncertain underlying causalities among network attack events, and the CCRP algorithm aims at dynamically updating the causality weights among different network attack events and attacker hypotheses based on alarm information and causal chain reasoning process. By causality simplification and causality reasoning methods, the CCRP efficiently predicts the attacker behaviors and potential attack likelihood under uncertain time-varying attack situations, and is robust to the incompleteness and redundancy in alarm information. Four experiments under different attack scenarios demonstrate that, the DUCAG model can effectively characterize and predict the complex and uncertain attack causalities, in a manner of high time efficiency. The proposed method has application significance on cloud computing platforms by dynamically evaluating network security status, predicting the future behaviors of attackers, and assisting in adjusting network defense strategies
Fabrication and Performance of UV Photodetector of ZnO Nanorods Decorated with Al Nanoparticles
In this work, localized surface plasmon resonance (LSPR) mediated by aluminum nanoparticles (Al NPs) was investigated to enhance the ultraviolet (UV) response of the zinc oxide nanorods (ZnO NRs) grown by the hydrothermal method. The ZnO NRs were characterized by scanning electron microscope, energy dispersive spectroscopy, X-ray diffractometer, Raman spectrometer, ultraviolet-visible spectrophotometer and fluorescence spectrometer. The results show that the morphology and crystalline structure of the ZnO NRs could not be changed before and after decoration with Al NPs, but the absorption rates in the UV range and the photoluminescence (PL) properties were improved. The photo-to-dark current ratio of ZnO NRs with Al NPs was about 447 for 325 nm UV light (5 mW/cm2) at 3.0 V bias, with the sensitivity increasing from 9.5 to 47.8, and the responsivity increasing from 53 to 267 mA/W
A privacyâpreserving method for publishing data with multiple sensitive attributes
Abstract The overgeneralisation may happen because most studies on data publishing for multiple sensitive attributes (SAs) have not considered the personalised privacy requirement. Furthermore, sensitive information disclosure may also be caused by these personalised requirements. To address the matter, this article develops a personalised data publishing method for multiple SAs. According to the requirements of individuals, the new method partitions SAs values into two categories: private values and public values, and breaks the association between them for privacy guarantees. For the private values, this paper takes the process of anonymisation, while the public values are released without this process. An algorithm is designed to achieve the privacy mode, where the selectivity is determined by the sensitive value frequency and undesirable objects. The experimental results show that the proposed method can provide more information utility when compared with previous methods. The theoretic analyses and experiments also indicate that the privacy can be guaranteed even though the public values are known to an adversary. The overgeneralisation and privacy breach caused by the personalised requirement can be avoided by the new method
A multiple sensitive attributes data publishing method with guaranteed information utility
Abstract Data publishing methods can provide available information for analysis while preserving privacy. The multiple sensitive attributes data publishing, which preserves the relationship between sensitive attributes, may keep many records from being grouped and bring in a high record suppression ratio. Another category of multiple sensitive attributes data publishing, which reduces the possibility of record suppression by breaking the relationship between sensitive attributes, cannot provide the sensitive attributes association for analysis. Hence, the existing multiple sensitive attributes data publishing fails to fully account for the comprehensive information utility. To acquire a guaranteed information utility, this article defines comprehensive information loss that considers both the suppression of records and the relationship between sensitive attributes. A heuristic method is leveraged to discover the optimal anonymity scheme that has the lowest comprehensive information loss. The experimental results verify the practice of the proposed data publishing method with multiple sensitive attributes. The proposed method can guarantee information utility when compared with previous ones
Secure sharing method of network data transmission based on multi-layer encryption technology
In order to ensure the effect of network data transmission in scientific research institutions and avoid network information from being attacked and damaged, a secure sharing method of network data transmission based on multi-layer encryption technology is proposed. Combined with multi-layer encryption technology, the network data transmission security protocol is constructed to ensure the security and integrity of the initial file. The network information transmission security evaluation system is further constructed. The network transmission path security of scientific research institutions is tracked, evaluated and tested in real time. The network data transmission security sharing platform is constructed to ensure the safe sharing of massive and complex data Experiments have proved that the security and sharing processing effect of the network data transmission security sharing method based on multi-layer encryption technology are significantly improved compared with the traditional methods, and fully meet the research requirements
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