Steady-state analysis of probabilistic Boolean networks

This paper investigates steady-state distributions of probabilistic Boolean networks via cascading aggregation. Under this approach, the problem is converted to computing least square solutions to several corresponding equations. Two necessary and sufficient conditions for the existence of the steady-state distributions for probabilistic Boolean networks are given firstly. Secondly, an algorithm for finding the steady-state distributions of probabilistic probabilistic Boolean networks is given. Finally, a numerical example is given to show the effectiveness of the proposed method.     

知识网络的构建过程分析

本文在分析组织存在知识缺口问题的基础上 ,指出了构建知识网络的实际意义 ,并进一步提出了知识网络构建过程中的构成要素、构建原则和构建方法。最后通过春兰集团的一个实际分析案例 ,说明了组织如何构建知识网络以及知识网络所体现的显著成效     

Aspect-based sentiment analysis with alternating coattention networks

Aspect-based sentiment analysis aims to predict the sentiment polarities of specific targets in a given text. Recent researches show great interest in modeling the target and context with attention network to obtain more effective feature representation for sentiment classification task. However, the use of an average vector of target for computing the attention score for context is unfair. Besides, the interaction mechanism is simple thus need to be further improved. To solve the above problems, this paper first proposes a coattention mechanism which models both target-level and context-level attention alternatively so as to focus on those key words of targets to learn more effective context representation. On this basis, we implement a Coattention-LSTM network which learns nonlinear representations of context and target simultaneously and can extracts more effective sentiment feature from coattention mechanism. Further, a Coattention-MemNet network which adopts a multiple-hops coattention mechanism is proposed to improve the sentiment classification result. Finally, we propose a new location weighted function which considers the location information to enhance the performance of coattention mechanism. Extensive experiments on two public datasets demonstrate the effectiveness of all proposed methods, and our findings in the experiments provide new insight for future developments of using attention mechanism and deep neural network for aspect-based sentiment analysis.     

Privacy in social networks: An analysis of Facebook

The only way to be aware of the risks and threats of Facebook, the most commonly used social networking site in the world and Turkey, is to be a careful user changing the default settings or simply not to have a Facebook account. In Turkey, there is still no study in which personal information shared though social networking sites has been evaluated in terms of privacy. For this reason, the findings obtained of this study have a great importance in the general picture of the current situation and drawing attention to the risks of the issue in Turkey where there are no legal arrangements effectively protecting the users from such sites. This study aims to investigate the Facebook privacy of information professionals who are members of KUTUP-L, and to determine the sensitivity and level of awareness of information professionals in Turkey. Facebook user profiles of 400 information professionals, all KUTUP-L members, have been analyzed in a study examining 32 different privacy settings. A privacy score has been calculated for each user, and the relations between privacy results have been analyzed. The findings at the end of the study show that information professionals in Turkey do pay attention to privacy, and most of the users change the default settings in order to protect their personal information.     

试论复杂网络分析方法在合作研究中的应用

科学合作的增加已经形成了大型的合作网络，迫切需要发展一种合适的网络计量方法。应用数学和统计物理学领域近年对复杂网络的演化和结构的研究已经证实，大多数的社会网络是具有共性的——“小世界”和“无标度”。合作网络可以说是一个真正的社会网络，因此也具有这些特性。简要介绍目前国际复杂网络分析方法及其在合作研究中的应用及前景。     

无线传感器网络LEACH协议的分析

在无线传感器网络中降低节点能耗,延迟网络生命周期是其研究的重点。现有分层路由协议中存在着簇首节点能耗分布不均,簇首与节点、基站间距离分布不均等问题;基于LEACH协议的思想提出一种改进的分层路由协议(M-LEACH),它考虑了簇首当前剩余能耗的因素,仿真结果表明能有效的延迟网络生命周期。     

广西公共建筑电气节能调查分析

电气节能,尤其是照明节能是公共建筑节能的重要组成部分。对广西几个主要城市公共建筑电能消耗及电气运行管理水平的现场调研结果进行分析及总结,并提出一些建议。     

Aspect sentiment analysis with heterogeneous graph neural networks

Aspect-based sentiment analysis technologies may be a very practical methodology for securities trading, commodity sales, movie rating websites, etc. Most recent studies adopt the recurrent neural network or attention-based neural network methods to infer aspect sentiment using opinion context terms and sentence dependency trees. However, due to a sentence often having multiple aspects sentiment representation, these models are hard to achieve satisfactory classification results. In this paper, we discuss these problems by encoding sentence syntax tree, words relations and opinion dictionary information in a unified framework. We called this method heterogeneous graph neural networks (Hete_GNNs). Firstly, we adopt the interactive aspect words and contexts to encode the sentence sequence information for parameter sharing. Then, we utilized a novel heterogeneous graph neural network for encoding these sentences’ syntax dependency tree, prior sentiment dictionary, and some part-of-speech tagging information for sentiment prediction. We perform the Hete_GNNs sentiment judgment and report the experiments on five domain datasets, and the results confirm that the heterogeneous context information can be better captured with heterogeneous graph neural networks. The improvement of the proposed method is demonstrated by aspect sentiment classification task comparison.     

企业创新网络的进化机制分析

结合相关企业案例,基于相关理论进展,初步分析我国企业创新网络进化的初始条件、总体趋向、动力机制、学习机制以及进化过程中的陷阱。在此基础上,尝试性地提出企业创新网络进化的一般模式。并就我国企业创新网络的发展提出几点建设性意见。     

Worst case analysis of resistive networks using linear programming approach

It is shown that for DC networks in which certain components are allowed to vary, the worst case DC problem can be solved by solving a linear programming problem. The constraints used in the linear programming problem are determined from the elements tolerance regions. This enables us to obtain the worst case solution without having to compute the gradient of the network functions.     

Passivity analysis of memristor-based recurrent neural networks with time-varying delays

This paper investigates the delay-dependent exponential passivity problem of the memristor-based recurrent neural networks (RNNs). Based on the knowledge of memristor and recurrent neural network, the model of the memristor-based RNNs is established. Taking into account of the information of the neuron activation functions and the involved time-varying delays, several improved results with less computational burden and conservatism have been obtained in the sense of Filippov solutions. A numerical example is presented to show the effectiveness of the obtained results.     

非专利引文衍生的科学期刊共被引网络分析

基于我国自1995-2004年间在美国专利和商标局(USPTO)获得授权的专利,用专利文献中的非专利引文作为构架科学与技术之间联系的桥梁,利用三种中心性指标对由我国USPTO专利所衍生出的科学期刊网络进行分析,从而探究了我国技术创新的科学基础。结果表明:三种著名的多学科科学期刊:PNAS,Science和Nature为我国技术创新提供了重要的科学基础。此外,一些化学类期刊也是我国专利技术主要的科学源。     

Improved exponential stability analysis for delayed recurrent neural networks

In this paper, we investigate the problem of global exponential stability analysis for a class of delayed recurrent neural networks. This class includes Hopfield neural networks and cellular neural networks with interval time-delays. Improved exponential stability condition is derived by employing new Lyapunov-Krasovskii functional and the integral inequality. The developed stability criteria are delay dependent and characterized by linear matrix inequalities (LMIs). The developed results are less conservative than previous published ones in the literature, which are illustrated by representative numerical examples.     

A theoretical analysis of the role of social networks in entrepreneurship

Entrepreneurship involves innovation and uncertainty. We outline a theory of entrepreneurship, which highlights the importance of social networks in promoting innovation and reducing uncertainty. Our findings suggest that this “social” aspect of entrepreneurship increases the probability of entrepreneurial success. The results also lend credence to theories of entrepreneurship that suggest that entrepreneurial opportunities are formed endogenously by the entrepreneurs who create them. We also consider the public policy implications of our findings.     

Adjacency matrix concepts for the analysis of the interconnection of networks

A mathematical theory is developed for an imagined device termed a “junctor”. A junctor could be used to interconnect two n-terminal networks giving rise to another n-terminal network. Actually a junctor is itself a simple network with three banks of n-terminals internally connected in some fashion by perfectly conducting wires. Adjacency matrices are formulated to analyze various junctors and their current flows. The main problem treated concerns conditions which would ensure that the junctor operation is associative.     

扬中工程电器行业专利的SWOT分析及对策研究

专利申请数量可以作为行业科技进步的风向标。本文将对扬中工程电器行业的专利进行SWTO分析,找出其优势、劣势、机会和威胁,提出解决问题的对策,将对企业和科研机构的研发、创新活动以及开展知识产权战略提供参考和帮助,以期促进扬中工程电器行业的可持续发展。     

Dementia analysis from functional connectivity network with graph neural networks

Deep learning methods have been widely applied for disease diagnosis on resting-state fMRI (rs-fMRI) data, but they are incapable of investigating global relationships between different brain regions as well as ignoring the interpretability. To address these issues, this paper presents a new graph neural network framework for brain disease diagnosis via jointly learning global relationships and selecting the most discriminative brain regions. Specifically, we first design a self-attention structure learning to capture the global interactions between brain regions for achieving diagnosis effectiveness, and theoretically integrate a feature selection method to reduce the noise influence as well as achieve interpretability. Experiment results on three neurological diseases datasets show the effectiveness of our method, compared to the comparison methods, in terms of diagnostic performance and interpretability.     

Destination buffer analysis for packets rejection obliteration in multi-channel networks

In this paper we study a multi-channel network, each station of which is equipped with a network interface that has a receiver buffer of multiple packets. In this way, each station is able to receive multiple packets per time instant. We adopt a synchronous access protocol which is affected by the collisions over the multiple channels and the destination conflicts. The proposed protocol performance crucially depends on the size of the receiver buffer since it determines the packet rejection probability at destination. An analytical probabilistic model based on a Markovian process is adopted for the performance measures derivation by means of closed mathematical formulas. The proposed protocol is compared to relative ones that either totally ignore the receiver collisions or assume a receiver buffer of a single packet capacity. The numerical results show that the increase of the receiver buffer size improves the performance decisively, resulting in higher throughput and lower delay and rejection probability. Also, it is shown that the appropriate receiver buffer size per station in order for the rejections at destination to be effectively eliminated is not unlimited but is limited to three packets for 0.1% accepted maximum level of rejection probability.     

产业生态网络模式的比较分析：一个实证研究

摘要：产业生态网络是产业活动在经济和资源环境上达到平衡的重要途径,是不同产业企业之间建立工业共生的组织表现形式。本文基于关联关系和空间分布两个维度,对产业生态网络的模式进行划分,并结合当前国内外工业共生的实践情况,从系统稳定性、技术创新能力、市场应变能力、成员参与程度、进入壁垒和环境绩效等方面对各自特点展开比较分析,对于加快我国生态工业建设具有指导意义。