强化会计内部控制促进高校科学管理

建立和强化完善的会计内部控制体系,对于高校优化资源,促进科学管理有着重要意义.针对当前高校会计内部控制的不足,提出了若干解决对策.     

微胞囊技术及产品F-500多功能灭火剂

介绍了微胞囊技术及产品F-500的灭火原理和优势。     

A novel methanol-tolerant Ir-Se chalcogenide electrocatalyst for oyxgen reduction

A novel methanol-tolerant oxygen-reduction catalyst, Iridium-selenium (Ir-Se) chalcogenide, was synthesized by chemical precipitation in an organic solvent. Auger electron spectroscopy (AES) analysis confirmed that the synthesized Ir-Se chalcogenide had a chemical formula of Ir₄Se. This chalcogenide showed strong catalytic activity towards the oxygen reduction reaction (ORR) and a high methanol tolerance. It was found that most of the oxygen could be directly reduced to water through a four-electron pathway with less than 10% hydrogen peroxide (H₂O₂) being produced during the ORR. The improvement in catalytic activity of the Ir-Se chalcogenide in comparison with that of pure Ir might be attributed to the effect of a bimetallic interaction.     

网络条件下的资本一般及其逻辑推演——利益、规则与标准

通过对资本一般概念的分析，结合资本一般的运动功能论述，认为在经济全球化和网络条件下，资本增值属性必然导致对规则和标准的争夺与控制，标准战是资本一般在新的经济社会形态下发展的必然逻辑结果。     

粘合剂流变特性的研究(待续)

本文从流变学的观点出发,分析粘合剂在配制及粘结过程中,反映出不同的流变特性,而粘合剂本身的流动、粘度、触变性与涂胶及其粘合的质量关系重大。     

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.     

基于逻辑器件的可编程增益放大器设计

本文介绍了可编程增益放大器设计的方法。它主要由控制电路、放大电路、显示电路三大模块组成。该系统性能好、成本低、工作可靠,具有一定的工程应用价值,经测试表明,该设计基本上达到了设计的要求。     

A conditional classification recurrent RBM for improved series mid-term forecasting

In the context of human-robot and robot-robot interactions, the better cooperation can be achieved by predicting the other party’s subsequent actions based on the current action of the other party. The time duration for adjustment is not sufficient provided by short term forecasting models to robots. A longer duration can by achieved by mid-term forecasting. But the mid-term forecasting models introduce the previous errors into the follow-up forecasting and amplified gradually, eventually invalidating the forecasting. A new mid-term forecasting with error suppression based on restricted Boltzmann machine(RBM) is proposed in this paper. The proposed model can suppress the error amplification by replacing the previous inputs with their features, which are retrieved by a deep belief network(DBN). Furthermore, a new mechanism is proposed to decide whether the forecasting result is accepted or not. The model is evaluated with several datasets. The reported experiments demonstrate the superior performance of the proposed model compared to the state-of-the-art approaches.

     

GRU-based capsule network with an improved loss for personnel performance prediction

Applied Intelligence - Personnel performance is a key factor to maintain core competitive advantages. Thus, predicting personnel future performance is a significant research domain in human...