PI-强LU富足半群

通过对C-L^U-富足半群的刻画,给出了PI-强L^U富足半群的结构定理。     

四螺旋创新集群:研究型大学人工智能发展生态重构与路向探究——以加拿大多伦多大学为例

以人工智能为代表的知识迭代发展,促使知识生产模式发生重大转变,催生了“大学—产业—政府—公众”四螺旋动力结构的建立和研究型大学知识生产新生态重构。以多伦多大学人工智能发展为例,考察其四螺旋利益相关主体及实践。从内在机理看,4个主体在互动运作中不仅重新确定了各自角色,而且还建立了大学(知识)—产业(产品)—政府(治理)—公众(公益)的新型逻辑链条,平衡公私利益格局,把公益指向作为人工智能四螺旋运作的中心目标;从外在特征看,4个主体形成了以大学为中心的区域创新网络,并牵引其他主体形成环高校创新集群。当前,我国在人工智能发展中不断发力,已进入世界第一方阵,但仍需要在国际比较学习中不断提升自身竞争力。基于案例分析,我国研究型大学发展人工智能有必要把握4个方面:一是走进中心,塑造大学在人工智能发展中的领导地位;二是以专促通,创新研究型大学人工智能专业培养模式;三是引企入研,提升校企合作人工智能创新的转化升级;四是人本导向,突出大学在人工智能发展中的公共价值。总体来看,我国研究型大学发展人工智能不仅要面临技术上的挑战,更要面临来自治理的挑战。     

An Economic Model-Based Matching Approach Between Buyers and Sellers Through a Broker in an Open E-Marketplace

A broker in an open e-marketplace enables buyers and sellers to do business with each other. Although a broker plays an important role in e-marketplaces, theory and guidelines for matching between buyers and sellers in multi-attribute exchanges are limited. Therefore, a challenge for a broker’s responsibility is how to maximize a buyer’s total satisfaction degree as its goals under the consideration of trade-off between a buyer’s buying quantity and price paid to a seller, and other attributes. To solve this challenge, this paper proposes an economic model-based matching approach between a buyer’s requirements and a seller’s offers. The major contributions of this paper are that (i) a broker can model a seller’s price policy as per a buyer’s buying quantity through communication between a broker and a seller; (ii) due to each buyer’s different quantity demand, a broker models a buyer’s satisfaction degree as per a buyer’s buying quantity based on communication between a broker and a buyer; and (iii) to carry out a broker’s matching processes, an objective function and a set of constraints are generated to help a broker to maximize a buyer’s total satisfaction degree. Experimental results demonstrate the good performance of the proposed approach.     

Study on the Centralization Strategy of the Blood Allocation Among Different Departments within a Hospital

By far, the researches on how to distribute blood products among different departments in hospital have not been further studied, though the problem of blood shortage and wastage that caused by improper blood allocation is severe, which may endanger patient’s lives and impose considerable costs on hospitals. In order to solve this problem, this paper mainly studies on how to distribute the blood items among different departments within a hospital and investigates the allocation approach with the novel management method by centralizing the inventory of several different departments. By integrating the blood inventory requirements of some departments, the hospital could reduce the rate of blood shortage and wastage effectively, release the pressure of the occupancy of resources and reduce the bullwhip effect of blood products. This paper illustrates the centralization principle in hospital and formulates the mixed integer programming model to work out the optimal allocation network scheme and the optimal inventory setting for every department. And the results of the numerical example demonstrate that this centralization method could considerably reduce blood shortage and wastage in hospital by about 72% and 90% respectively. Furthermore, it could decrease the total cost by about 108,540 RMB a month on blood supply chain management in the hospital and improve the effect of some certain surgeries by transfusing the fresh blood to patients.     

Effects of Strain Rate,Temperature and Grain Size on the Mechanical Properties and Microstructure Evolutions of Polycrystalline Nickel Nanowires: A Molecular Dynamics Simulation

Through molecular dynamics(MD)simulation,the dependencies of temperature,grain size and strain rate on the mechanical properties were studied.The simulation results demonstrated that the strain rate from 0.05 to 2 ns~(–1 )affected the Young’s modulus of nickel nanowires slightly,whereas the yield stress increased.The Young’s modulus decreased approximately linearly;however,the yield stress firstly increased and subsequently dropped as the temperature increased.The Young’s modulus and yield stress increased as the mean grain size increased from 2.66 to6.72 nm.Moreover,certain efforts have been made in the microstructure evolution with mechanical properties association under uniaxial tension.Certain phenomena such as the formation of twin structures,which were found in nanowires with larger grain size at higher strain rate and lower temperature,as well as the movement of grain boundaries and dislocation,were detected and discussed in detail.The results demonstrated that the plastic deformation was mainly accommodated by the motion of grain boundaries for smaller grain size.However,for larger grain size,the formations of stacking faults and twins were the main mechanisms of plastic deformation in the polycrystalline nickel nanowire.     

Fuzzy Views on Black-Litterman Portfolio Selection Model

In this paper, views of investor are described in fuzzy sets, and two fuzzy Black-Litterman models are constructed with fuzzy views and fuzzy random views respectively. In the models, expected returns and uncertainty matrix of views are redefined and the views are formulated by fuzzy approaches suitably. Then the models are tested with data from Chinese financial markets. Empirical results show that the fuzzy random views model performs the best, and both the fuzzy models are better than the traditional ones, demonstrating that the fuzzy approaches can contain more information in the views and measure the uncertainty more correctly.     

高温作用后砂岩物理力学性质阈值温度的确定——基于机器学习算法

通过采用机器学习算法，提出了高温作用后砂岩物理力学性质变化的阈值温度的确定方法。基于Python语言，利用K-Means、SVM算法，实现了对样本数据的分类和聚类，确定了阈值温度区间，验证了二分类法的合理性和准确性.结果表明，砂岩样本的阈值温度区间为400~600 ℃，阈值温度上下砂岩的物理力学性质存在显著差异，体现为阈值温度区间以下的岩样物理力学性质较为分散，而阈值温度区间以上的岩样物理力学性质较为集中.     

Aristotle Said “Happiness is a State of Activity” — Predicting Mood Through Body Sensing with Smartwatches

We measure and predict states of Activation and Happiness using a body sensing application connected to smartwatches. Through the sensors of commercially available smartwatches we collect individual mood states and correlate them with body sensing data such as acceleration, heart rate, light level data, and location, through the GPS sensor built into the smartphone connected to the smartwatch. We polled users on the smartwatch for seven weeks four times per day asking for their mood state. We found that both Happiness and Activation are negatively correlated with heart beats and with the levels of light. People tend to be happier when they are moving more intensely and are feeling less activated during weekends. We also found that people with a lower Conscientiousness and Neuroticism and higher Agreeableness tend to be happy more frequently. In addition, more Activation can be predicted by lower Openness to experience and higher Agreeableness and Conscientiousness. Lastly, we find that tracking people’s geographical coordinates might play an important role in predicting Happiness and Activation. The methodology we propose is a first step towards building an automated mood tracking system, to be used for better teamwork and in combination with social network analysis studies.     

EVOKE: A Value-Driven Concept Selection Method for Early System Design

The development of new technologically advanced products requires the contribution from a range of skills and disciplines, which are often difficult to find within a single company or organization. Requirements establishment practices in Systems Engineering (SE), while ensuring coordination of activities and tasks across the supply network, fall short when it comes to facilitate knowledge sharing and negotiation during early system design. Empirical observations show that when system-level requirements are not available or not mature enough, engineers dealing with the development of long lead-time sub-systems tend to target local optima, rather than opening up the design space. This phenomenon causes design teams to generate solutions that do not embody the best possible configuration for the overall system. The aim of this paper is to show how methodologies for value-driven design may address this issue, facilitating early stage design iterations and the resolution of early stage design trade-offs. The paper describes how such methodologies may help gathering and dispatching relevant knowledge about the ‘design intent’ of a system to the cross-functional engineering teams, so to facilitate a more concurrent process for requirement elicitation in SE. The paper also describes EVOKE (Early Value Oriented design exploration with KnowledgE maturity), a concept selection method that allows benchmarking design options at sub-system level on the base of value-related information communicated by the system integrators. The use of EVOKE is exemplified in an industrial case study related to the design of an aero-engine component. EVOKE’s ability to raise awareness on the value contribution of early stage design concepts in the SE process has been further verified with industrial practitioners in ad-hoc design episodes.