推理能力、认知方式和启发量对顿悟问题解决不同阶段的影响

从《科学发明创造实验问题材料库》中选取实验材料,采用"学习多个原型-测试多个问题"的两阶段实验范式,探究推理能力、认知方式和启发量对顿悟问题解决中原型激活与关键启发信息提取这两个阶段的影响。结果发现:(1)高推理能力被试比低推理能力被试的顿悟问题解决水平更高,且高推理能力被试在原型激活和关键启发信息提取上都显著优于低推理能力被试;(2)认知方式对原型激活和关键启发信息提取均没有影响;(3)启发量对原型激活没有影响,但对关键启发信息的提取有影响,并且高启发量的原型比低启发量的原型更能促进关键启发信息的提取。

发明创造问题解决中的原型位置效应

以科学发明创造问题为实验材料,采用"一对一"实验范式,对发明创造问题解决中的原型位置效应进行探讨,结果发现:(1)原型位置主效应显著,后呈现原型成绩显著优于先呈现原型;(2)原型位置效应受创造性倾向影响,随创造性倾向的提高而显著降低;(3)原型位置效应不受启发量影响,但不同创造性个体受高低启发量影响;(4)发明创造问题解决得分与创造性倾向总分相关显著,二者在原型位置效应上表现相同的效应。

Chinese multi-document personal name disambiguation

This paper presents a new approach to determining whether an interested personal name across doeuments refers to the same entity. Firstly,three vectors for each text are formed： the personal name Boolean vectors denoting whether a personal name occurs the text the biographical word Boolean vector representing title, occupation and so forth, and the feature vector with real values. Then, by combining a heuristic strategy based on Boolean vectors with an agglomeratie clustering algorithm based on feature vectors, it seeks to resolve multi-document personal name coreference. Experimental results show that this approach achieves a good performance by testing on ＂Wang Gang＂ corpus.

An Uncertain Programming Model for Land Use Structure Optimization to Promote Effectiveness of Land Use Planning

Land use structure optimization(LUSO) is an important issue for land use planning. In order for land use planning to have reasonable flexibility, uncertain optimization should be applied for LUSO. In this paper, the researcher first expounded the uncertainties of LUSO. Based on this, an interval programming model was developed, of which interval variables were to hold land use uncertainties. To solve the model, a heuristics based on Genetic Algorithm was designed according to Pareto Optimum principle with a confidence interval under given significance level to represent LUSO result. Proposed method was applied to a real case of Yangzhou, an eastern city in China. The following conclusions were reached. 1) Different forms of uncertainties ranged from certainty to indeterminacy lay in the five steps of LUSO, indicating necessary need of comprehensive approach to quantify them. 2) With regards to trade-offs of conflicted objectives and preferences to uncertainties, our proposed model displayed good ability of making planning decision process transparent, therefore providing an effective tool for flexible land use planning compiling. 3) Under uncertain conditions, land use planning effectiveness can be primarily enhanced by flexible management with reserved space to percept and hold uncertainties in advance.

A Heuristic Algorithm on QoS Routing

This paper focuses on solving the delay constrained least cost routing problem, and propose a simple, distributed heuristic solution, called distributed recursive delay constrained least cost (DR DCLC) unicast routing algorithm. DR DCLC only requires local information to find the near optimal solution. The correctness of DR DCLC is proued by showing that it is always capable of constructing a loop free delay constrained path within finite time, if such a path exists. Simulation is also used to compare DR DCLC to the optimal DCLC algorithm and other algorithms.

Energy-constrained ferry route design for sparse wireless sensor networks

In recent years,using message ferries as mechanical carriers of data has been shown to be an effective way to collect information in sparse wireless sensor networks.As the sensors are far away from each other in such highly partitioned scenario,a message ferry needs to travel a long route to access all the sensors and carry the data collected from the sensors to the sink.Typically,practical constraints(e.g.,the energy)preclude a ferry from visiting all sensors in a single tour.In such case,the ferry can only access part of the sensors in each tour and move back to the sink to get the energy refilled.So,the energy-constrained ferry route design(ECFRD)problem is discussed,which leads to the optimization problem of minimizing the total route length of the ferry,while keeping the route length of each tour below a given constraint.The ECFRD problem is proved to be NP-hard problem,and the integer linear programming(ILP)formulation is given.After that,efficient heuristic algorithms are proposed to solve this problem.The experimental results show that the performances of the proposed algorithms are effective in practice compared to the optimal solution.

Energy Efficient Switch Policy for Small Cells

Switch policy is essential for small cells to properly serve variable number of users in an energy efficient way.However,frequently switching small cell base stations(SBSs) may increase the network operating cost,especially when there is an nonnegligible start-up energy cost.To this end,by observing the variety of user number,we focus on the design of a switch policy which minimize the cumulative energy consumption.A given user transmission rate is guaranteed and the capability of SBSs are limited as well.According to the knowledge on user number variety,we classify the energy consumption problem into two cases.In complete information case,to minimize the cumulative energy consumption,an offline solution is proposed according to critical segments.A heuristic algorithm for incomplete information case(HAIIC) is proposed by tracking the difference of cumulative energy consumption.The upper bound of the Energy Consumption Ratio(ECR) for HAIIC is derived as well.In addition,a practical Q-learning based probabilistic policy is proposed.Simulation results show that the proposed HAIIC algorithm is able to save energy efficiently.

High Energy ^-pp and pp Elastic Scatterings in QCD Inspired Model

We propose QCD inspired model to calculate ^-pp and pp elastic scatterings at high energies in this paper. A calculation for total cross section of ^-pp and pp is performed in which the contributions from gluon-gluon, quark-quark, and gluon-quark interactions are included. Our results show that the QCD inspired model gives a perfect fit to experimental data of total cross section both for ^-pp and pp elastic scatterings at the whole energy region where experimental data existed at FNAL and CERN.

Accuracy characterization and measurement point planning for workpiece localization

This paper addresses the problem of accuracy characterization and measurement point planning for 3-D workpiece localization in the presence of part surface errors and measurement errors. Two frame-invariant functions of the infinitesimal rigid body displacement are defined to quantify the localization accuracy required by manufacturing processes. Then, two kinds of frame-invariant indices are derived to characterize the sensitivities of the accuracy measures to the sampling errors at the measurement points. With a dense set of discrete points on the workpiece datum surfaces pre-defined as candidates for measurement, planning of probing points for accurate recovery of part location is modeled as a combinatorial problem focusing on minimizing the accuracy sensitivity index. Based on an interchange rule, a greedy algorithm is developed to efficiently find a near-optimal solution. It is also shown that if the number of the measurement points is sufficiently large, there is no need to optimize their positions. Example confirms the validity of the presented indices and algorithm. Keywords localization - fixture - accuracy - uncertainty assessment - measurement planning - optimal design - heuristic algorithm