温度,压力对漂移室气体增益的影响

研究了温度及气体压力对漂移室（工作于正比区）气体放大倍数的影响，温度和气体压力的变化范围分别是５￣４０℃及９０￣１０５ｋＰａ。用实验数据拟合得到了函数关系并测量了几种饱和度下函数中的参数值。     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

Authority updating: An expert authority evaluation algorithm considering post‐evaluation and power indices in social networks

In group assessment, the focus is on finding high‐authority experts to improve the reliability of assessment results. In this study, we propose an authority updating algorithm while considering the power and judgement reliability of an expert on the basis of social networks and post‐evaluations. A network power index is established and used to reflect the power of an expert while considering social networks. The measurement of the judgement reliability of an expert considers the post‐evaluation of the objects selected by experts, thereby more scientifically reflecting the reliability of experts. The analysis shows the following: although the social‐network structure influences the authority of experts, the influence weakens when the assessment group is a highly or even fully connected group; the network effect may increase the authority of some experts and reduce that of others, and it will weaken as the network connectivity increases; moreover, the judgement reliability and authority of an expert while considering post‐evaluation can encourage him/her to make fair assessments and strive to reduce his/her motivation and cognitive biases.     

Protect privacy of deep classification networks by exploiting their generative power

Machine Learning - Research showed that deep learning models are vulnerable to membership inference attacks, which aim to determine if an example is in the training set of the model. We propose a...     

Granular multiple kernel learning for identifying RNA-binding protein residues via integrating sequence and structure information

Neural Computing and Applications - RNA-binding proteins play an important role in the biological process. However, the traditional experiment technology to predict RNA-binding residues is...     

Analysis of emerging technology adoption for the digital content market

The digital content market is undergoing an evolution in networking and digitalization technologies, offering diverse information and services. Due to the characteristics of these emerging technologies, the digital content market is growing rapidly and traditional content providers face service transformation decisions. While a majority of the previous technology adoption studies have focused on the viewpoints of users and customers, cost reduction, or electronic channel related technologies, in this research we analyze the emerging technology adoption decisions of competing firms for providing new content services from a strategic perspective. Utilizing game theoretical models, we examine the effects of market environments (technology cost, channel cannibalization, brand power, brand extension, information asymmetry and market uncertainty) on firms’ adoption decisions. This research contributes a number of unique and interesting implications for the issues of emerging technology adoption for new content service provision.     

Adaptive synchronization of master-slave large-scale systems against bias actuators and network attenuations

This paper utilizes the adaptive technique to design a class of active synchronizing masterslave large scale systems against imperfect actuators and networked interconnections with bias faults and signal attenuations, respectively. Without the requirement of knowledge of eventual faulty factors of bias-actuators on systems, and attenuation factors of connected networks, an adaptive mechanism is designed to estimate each unknown faulty factor on-line for constructing a class of distributed adaptive controllers. Then based on the adaptive adjustment parameters and Lyapunov stability theory, Lyapunov functions are addressed to prove that the proposed adaptive master-slave large-scale system can be guaranteed to be asymptotic synchronization with the improper actuator and faulty transmitted signals. Finally, a multiple vehicle large-scale system is used to verify the efficiency of the method.     

Preparation and properties of close-packed composite materials

Monodisperse silica particles of about 0.3m diameter are suspended in methacrylate monomer using a carefully selected dispersant. Many steric dispersants are hydrocarbon chains with a reactive end-group. These are not effective as dispersants for silica in moderately polar solvents, such as esters and the methacrylate monomers. Good dispersion was obtained with a methacrylate polymer terminated by a chlorosilane end group. Settling or centrifugation of these unagglomerated dispersions gives well-packed particle beds. Polymerization of the surrounding monomer produces composite materials with high packing fractions and a high degree of regularity. Moduli and strengths of these composites are reported.     

文科《多媒体技术与应用》课程设置与教学研究

多媒体技术是以数字技术为基础的综合技术。本文结合文科学生的特点,探讨了《多媒体技术与应用》课程设置与教学。     

Pd/Mg(OH)2 Heterogeneous Nanocatalysts Synthesized by a Facile One-Pot Hydrothermal Method for CO Direct Esterification to Dimethyl Oxalate

Catalysis Letters - Pd-based heterogeneous nanocatalysts have wide application in chemical industry. However, the traditional synthesis process contains multi-steps such as impregnation, dry,...