GF(2)上本原多项式的三项倍式的次数研究

研究了二元域上本原多项式的三项倍式的计数问题,通过对三项倍式进行分类,导出了本原多项式三项倍式最低次数的一个上界.利用这一结果,使构造本原多项式的次数最低的三项倍式的计算复杂性降到原来的九分之一.     

专利法第33条在专利申请及审查中的重要性

专利审查部门与实务界针对《专利法》第33条规定的“修改不得超范围”原则一直存在较多分歧与争论,并且上述分歧及矛盾在某种程度上并未得到有效解决.从专利审查员的审查意见及申请人的意见陈述两个层面出发,对若干实际案例做出具体分析,目的在于表明上述分歧及矛盾并非不可调和,双方可通过在审查意见及意见陈述中合理运用专利法第33条以使申请人的利益得到切实维护.     

Quality perception when streaming video on tablet devices

The proposed work aims at analyzing the quality perceived by the user when streaming video on tablet devices. The contributions of this paper are: (i) to analyze the results of subjective quality assessments to determine which Quality of Service (QoS) parameters mainly affect the users’ Quality of Experience (QoE) in video streaming over tablet devices; (ii) to define a parametric quality model useful in system control and optimization for the considered scenarios; (iii) to compare the performance of the proposed model with subjective quality results obtained in alternative state-of-the-art studies and investigate whether other models could be applied to our case and vice versa.     

基于强化学习的合作频谱分配算法

为了解决认知无线电网络中的频谱分配问题,提出了一种基于用户体验质量的合作强化学习频谱分配算法,将认知网络中的次用户模拟为强化学习中的智能体,并在次用户间引入合作机制,新加入用户可以吸收借鉴其他用户的强化学习经验,能够以更快的速度获得最佳的频谱分配方案;并且在频谱分配过程中引入了主用户和次用户之间的价格博弈因素,允许主用...     

基于社会网络的舆情传播模型构建与分析

本文考虑个体间的相互作用,提出了一个基于社会网络分析的舆情传播模型.模型假设网络中每个个体的初始状态只有两种情况,并且在单位时间步内只选择一个邻居进行交流,并以概率λ接受该邻居的意见.解析结果显示存在概率λc使得网络中持某种观点人数比例的期望值是一个常数,而其它状态下系统中所有个体的意见都会达成一致.本模型有助于衡量某给定社会网络中舆论传播的快慢程度.     

一种研究网络论坛上舆论演化的新方法

在网络论坛上,以某一话题为中心的网络舆论已经成为影响人们生活,甚至政府决策的重要因素.话题的参与者以论坛的方式组合在一起,通过相互之间信息的交互,逻辑上形成动态变化的系统.由于人类本身的适应性(对环境的适应),从而造成该系统的错综复杂,谁都无法把握该系统的发展.为此,引入复杂适应性系统的思想和方法,通过对基于论坛的网络舆论的分析,将影响该类网络舆论形成、发展的几个重要因素进行规则化.以CAS理论来构建基于论坛的网络舆论系统并研究其演化,并利用Swarm平台对该系统进行实现.实验仿真结果表明CAS理论能够有效地研究基于论坛的网络舆论,为进一步研究互联网上的网络舆论提供新的方法.     

Public Attitudes Toward Nanotechnology

Data from 3909 respondents to an Internet survey questionnaire provide the first insights into public perceptions of nanotechnology. Quantitative analysis of statistics about agreement and disagreement with two statements, one positive and the other negative, reveals high levels of enthusiasm for the potential benefits of nanotechnology and little concern about possible dangers. The respondents mentally connect nanotechnology with the space program, nuclear power, and cloning research, but rate it more favorably. In contrast, they do not associate nanotechnology with pseudoscience, despite its imaginative exploitation by science fiction writers. Qualitative analysis of written comments from 598 respondents indicates that many ideas about the value of nanotechnology have entered popular culture, and it provides material for an additional 108 questionnaire items that can be used in future surveys on the topic. The findings of this exploratory study can serve as benchmarks against which to compare results of future research on the evolving status of nanotechnology in society.     

Subset selection for the least probable multinomial cell

Summary An inverse sampling procedureR is proposed for selecting a randomsize subset which contains the least probable cell (i.e., the cell with the smallest cell probabilities) from a multinomial distribution withk cells. Type 2-Dirichlet integrals are used (i) to express the probability of a correct selection in terms of integrals with parameters only in the limits of integration, (ii) to prove that the least favorable configuration underR is the so-called slippage configuration withk equal cell probabilities, and (iii) to express exactly the expectation of the total number of observations required and the expectation of the subset size under the procedureR.     

Iterative behaviour of generalized majority functions

Let us consider a society of n persons {P₁,…,P_n} with interaction coefficient a_ij between P_i and P_j. Let {θ₁,…,θ_p} be the set of opinions which may be assumed by any person. We study the dynamical behaviour of such a society under local majority rules.The results presented in this paper generalize many partial results previously obtained by several authors (Tchuente, 1977; Goles and Olivos, 1980; Poljak and Sura, 1982). Furthermore, by introducing algebraic invariants, analogous to those exhibited in Goles (1980) for the study of Boolean threshold functions, we provide a tool for a general approach of such dynamical models.     

ORuML: Optimized Routing in wireless networks using Machine Learning

Routing is a process of selecting a path in a network for delivering a packet from source node to destination node. Successful delivery of a message is a challenge, and therefore, this paper proposes an algorithm for a wireless network called Optimized Routing in wireless networks using Machine Learning (ORuML), which uses machine learning algorithm namely, K‐nearest neighbor (KNN), Support Vector Machine (SVM), and Multinomial Logistic Regression (MLR), to predict the network type of the source and destination nodes. The ML model is trained by using characteristic features of a node collected in real time such as battery power utilization, available internal storage, IP address, and range of a node. Intuitively, the MLR should outperform KNN and SVM in terms of accuracy and Area under ROC Curve (AUC). The proposed algorithm determines whether the source and destination nodes are co‐located and also, determines the best neighboring hop for efficient routing.