怎样利用Internet上的Whois服务来查找个人信息

对Ｉｎｔｅｒｎｅｔ上的找人服务Ｗｈｏｉｓ的两种基本情况ＩｎｔｅｒＮＩＣ的Ｗｈｏｉｓ服务和其它机构的Ｗｈｏｉｓ服务进行了介绍;对如何利用Ｗｅｂ方式以及客户程序ＷｉｎＷｈｏｉｓ来查换Ｗｈｏｉｓ服务器中的信息作了较详细的说明;最后对使用Ｗｈｏｉｓ服务需要注意的地方作了讨论。     

多总线与AT总线的接口技术

提出了以ＩＢＭ－ＰＣ／ＡＴ计算机为主控机的Ｍｕｌｔｉｂｕｓ系统总线的设计，讨论了ＩＢＭ－ＰＣ／ＡＴ计算机和Ｍｕｌｔｉｂｕｓ之间的时序配合及有关的总线扩展技术。该方案也可广泛地应用于以Ｍｕｌｔｉｂｕｓ为总线的其它系统中。     

信息资源数据库CBT系统的实现方法

信息资源是人类的宝贵财富,数据库技术是管理信息资源的现代化工具。掌握信息资源数据库的理论方法和实用技术是知识经济时代的需要。本文讨论了《数据库原理》课程教学的ＣＢＴ（Ｃｏｍｐｕｔｅｒ Ｂａｓｅｄ Ｔｒａｉｎｉｎｇ）系统设计过程与实现方法。     

几种一维原子链晶格振动特性比较研究

本文从结构、态密度和本征波函数三个方面系统研究了单原子周期链、双原子周期链、无序链、纳米链、Ｆｉｂｏｎａｃｃｉ准晶链和Ｔｈｕｅ－Ｍｏｒｓｅ链六种一维体系的晶格振动特性，给出并讨论了他们的区别和联系。     

刻度指数族参数的经验Bayes检验的收敛速度

在“加权线性损失”下讨论刻度指数族中参数的经验Ｂａｙｅｓ（ＥＢ）检验问题．利用基于 Ｂｅｓｓｅｌ函数的核估计方法构造了ＥＢ检验函数．在适当的条件下证明了获得的ＥＢ检验函数是渐近最优的具有收敛速度Ｏ（ｎ－１ｌｎ６ ｎ）．最后给出一个满足定理条件的例子．     

最优消费投资的动态经济模型的进一步研究

金融市场上的债券和股票价格瞬息万变。对这种复杂的变动趋势我们可以用随机微分方程加以描述，并据此来研究投资者的最优消费与投资决策。Ｋａｒａｔｚａｓ［１］给出了债券和股票价格的动态模型，该模型反映了价格与债券的利息率ｒ（ｔ）、股票的回报率ｂ（ｔ）及扩散矩阵σ（ｔ）等联系的动态模型。当投资者同时参与消费时，考虑到效用函数Ｕ及贴现函数β（ｔ），Ｋａｒａｔｚａｓ又研究了最优消费与投资公式，由于Ｋａｒａｔｚａｓ讨论的β（ｔ）仅为常数，显然有很大的局限性。为此在文献［３］中就β（ｔ）为有限分段和无穷分段函数两种情形推广了Ｋａｒａｔｚａｓ的结果。本文就β（ｔ）为连续函数情形进行进一步推广     

无扰Polysilane链的热力学函数

采用旋转异构态模型和二级相互作用近似，计算了无扰Ｐｏｌｙｓｉｌａｎｅ链的内能、自由能和熵，讨论了它们与链长和温度的关系     

风险避免型决策风险金模型与应用

风险避免型决策风险金模型与应用朱玉旭（上海交通大学管理学院２０００３０）１引言以冯诺曼一摩根斯坦（ＶｏｎＮｏｒｍａｎｎ一Ｍｏｒｇｅｎｓｔａｎ，以下简作ＷＭ）的期望效用值理论为基础发展起来的风险决策理论在各领域中得到日益广泛的应用。本文主要讨论风险避免...     

一维Logistic映射的分形维数

针对一维Ｌｏｇｉｓｔｉｃ映射与初值的关系,讨论了一维映的分形曲线,计算得出分形维数Ｄ值按几何级数收敛,且收敛速率β＝３．１２７。     

新产品市场扩散Bas模型族的研究

本文对Ｂａｓｓ模型及其扩展型的结构、特征（包括拐点、对称性和量纲）和内在联系进行了较全面的比较分析,为进一步研究新产品扩散模型提供了方法上的指导     

Query Generation and Buffer Mechanism: Towards a better conversational agent for legal case retrieval

In legal case retrieval, existing work has shown that human-mediated conversational search can improve users’ search experience. In practice, a suitable workflow can provide guidelines for constructing a machine-mediated agent replacing of human agents. Therefore, we conduct a comparison analysis and summarize two challenges when directly applying the conversational agent workflow in web search to legal case retrieval: (1) It is complex for agents to express their understanding of users’ information need. (2) Selecting a candidate case from the SERPs is more difficult for agents, especially at the early stage of the search process. To tackle these challenges, we propose a suitable conversational agent workflow in legal case retrieval, which contains two additional key modules compared with that in web search: Query Generation and Buffer Mechanism. A controlled user experiment with three control groups, using the whole workflow or removing one of these two modules, is conducted. The results demonstrate that the proposed workflow can actually support conversational agents working more efficiently, and help users save search effort, leading to higher search success and satisfaction for legal case retrieval. We further construct a large-scale dataset and provide guidance on the machine-mediated conversational search system for legal case retrieval.     

Inertia and scaling in deterministic lateral displacement

The ability to separate and analyze chemical species with high resolution, sensitivity, and throughput is central to the development of microfluidics systems. Deterministic lateral displacement (DLD) is a continuous separation method based on the transport of species through an array of obstacles. In the case of force-driven DLD (f-DLD), size-based separation can be modelled effectively using a simple particle-obstacle collision model. We use a macroscopic model to study f-DLD and demonstrate, via a simple scaling, that the method is indeed predominantly a size-based phenomenon at low Reynolds numbers. More importantly, we demonstrate that inertia effects provide the additional capability to separate same size particles but of different densities and could enhance separation at high throughput conditions. We also show that a direct conversion of macroscopic results to microfluidic settings is possible with a simple scaling based on the size of the obstacles that results in a universal curve.     

基于Rough集理论的新型软件测试工具研究

根据对现行软件测试用例设计方法,结合人工智能领域知识和方法,提出一种应用谓词演算方法进行软件测试用例的设计方法。通过谓词演算,自动设计软件测试用例,提供给测试员以详细参考。     

Strategic repositioning by means of alliance networks: The case of IBM

This paper aims to show that alliance networks can play an important role in facilitating large-scale strategic change projects. It focuses on the particular case of IBM, whose radical redirection from an exploitation strategy towards an exploration strategy was realized by major changes in its network strategy. We show that by involving new partners in the network and by loosening the ties with its existing partners, IBM managed to transform from a hardware manufacturing company to a global service provider and software company. The findings suggest that the traditional view of large firms as being slow to adapt may not be valid because alliance networks can be used to overcome inertia.     

Legal case document similarity: You need both network and text

Estimating the similarity between two legal case documents is an important and challenging problem, having various downstream applications such as prior-case retrieval and citation recommendation. There are two broad approaches for the task — citation network-based and text-based. Prior citation network-based approaches consider citations only to prior-cases (also called precedents) (PCNet). This approach misses important signals inherent in Statutes (written laws of a jurisdiction). In this work, we propose Hier-SPCNet that augments PCNet with a heterogeneous network of Statutes. We incorporate domain knowledge for legal document similarity into Hier-SPCNet, thereby obtaining state-of-the-art results for network-based legal document similarity.Both textual and network similarity provide important signals for legal case similarity; but till now, only trivial attempts have been made to unify the two signals. In this work, we apply several methods for combining textual and network information for estimating legal case similarity. We perform extensive experiments over legal case documents from the Indian judiciary, where the gold standard similarity between document-pairs is judged by law experts from two reputed Law institutes in India. Our experiments establish that our proposed network-based methods significantly improve the correlation with domain experts’ opinion when compared to the existing methods for network-based legal document similarity. Our best-performing combination method (that combines network-based and text-based similarity) improves the correlation with domain experts’ opinion by 11.8% over the best text-based method and 20.6% over the best network-based method. We also establish that our best-performing method can be used to recommend/retrieve citable and similar cases for a source (query) case, which are well appreciated by legal experts.     

Big data analytics and international negotiations: Sentiment analysis of Brexit negotiating outcomes

We introduce Big Data Analytics (BDA) and Sentiment Analysis (SA) to the study of international negotiations, through an application to the case of the UK-EU Brexit negotiations and the use of Twitter user sentiment. We show that SA of tweets has potential as a real-time barometer of public sentiment towards negotiating outcomes to inform government decision-making. Despite the increasing need for information on collective preferences regarding possible negotiating outcomes, negotiators have been slow to capitalise on BDA. Through SA on a corpus of 13,018,367 tweets on defined Brexit hashtags, we illustrate how SA can provide a platform for decision-makers engaged in international negotiations to grasp collective preferences. We show that BDA and SA can enhance decision-making and strategy in public policy and negotiation contexts of the magnitude of Brexit. Our findings indicate that the preferred or least preferred Brexit outcomes could have been inferred by the emotions expressed by Twitter users. We argue that BDA can be a mechanism to map the different options available to decision-makers and bring insights to and inform their decision-making. Our work, thereby, proposes SA as part of the international negotiation toolbox to remedy for the existing informational gap between decision makers and citizens’ preferred outcomes.     

Do instant messaging interruptions help or hinder knowledge workers’ task performance?

The modern workplace environment is filled with interruptions due to the necessity of coworkers to communicate with each other. Studies have revealed that interruptions can impact task performance (TP). Communication interruptions are due, in part, to the unavoidable side-effect of using technology to facilitate these interactions. This experimental case study reports about an investigation we conducted on the role of instant messaging interruptions (IMI) and its implications on knowledge workers’ TP in a workplace environment. We have gathered data from knowledge workers engaged in an e-learning activity. The case study included a total of 60 experimental observations and analysis of the 120 records revealed that the time to complete a task (TPtct) for certain types of tasks, was significantly affected by IMI. This case study addressed gaps in IM interruption research and practical knowledge about the role of instant messages in the organization. Previous research has been conducted in a laboratory environment with interruptions generated by means other than actual IM. This case study used IMI with participants working in their normal workplace. Findings were used to provide a set of lessons learned recommendations for managers when it comes to the use of IM in the workplace.     

Software product evolution for Intellectual Capital Management: The case of Meta4 PeopleNet

Software must evolve in order to adapt to new demands and scenarios. In the case of packaged software that can be customized, this evolution implies the maintenance of both out-of-the-box and customized functionality alike. New user interface technologies provide a way to interact with applications that software vendors are forced to incorporate in order to meet new user and market requirements. Packaged software vendors are facing software evolution processes in order to attract more customers and conserve the existing ones. This case analysis describes the evolution of packaged software, Meta4 PeopleNet, towards the addiction of Rich Internet Applications features to a Human and Intellectual Capital Management tool. The findings and lessons learned presented in this case study provide useful insights for packaged software vendors facing software product evolution.     

Towards cost efficient mobile service and information management in ubiquitous environment with cloud resource scheduling

The past few years have witnessed an explosive popularity of mobile services, especially in the form of smart phone applications. To cope with the limited batteries and computational capacities of mobile devices, prior studies suggest to deploy service instances in clouds for accomplishing most of the computation-intensive tasks. Service composition, which compensates for the simplicity of single service, is an effective way to utilize the plentiful services on the clouds all over the world. In this paper, we focus on the problem of service instance selection with service instance replica limitation constraint. The objective is to select the optimal set of service instances, which composes the integrated service and brings out the optimal QoS (quality of service), in terms of service response time. To characterize the problem, we establish a new QoS model, which considers the comprehensive quality over all users, not just for any single user or service instance. We prove that the problem is NP-hard, since many functionally equivalent service instances spread all over the distributed clouds. To address the problem, we classify the problem into three cases, including two special cases and the general case. We present two effective heuristic algorithms to determine the service instances selection for the two special cases, which are still NP-hard. The two special cases provide empirical bounds for the general case. We propose an algorithm that simulates a vote procedure for the users in the general case. The selected service instances, which come from the vote procedure, can satisfy a majority of users. We conduct extensive simulations for all of the algorithms. The simulation results show that our algorithms work efficiently on service response time reduction.     

Towards a taxonomy of research misconduct: The case of business school research

This paper examines the growing pressures and incentives encouraging research misconduct, along with the consequences, as illustrated by the case of business school research. Drawing on a review of the literature on different theoretical approaches to analysing organizational misconduct, we develop a formal taxonomy distinguishing appropriate conduct from blatantly inappropriate misconduct but with a specific focus on the ‘grey’ areas between these extremes in the form of questionable and inappropriate behaviour. We identify various sources of research misbehaviour and different categories of those affected. The aim is to provide a clearer understanding of what research behaviour is deemed appropriate or not, which stakeholders it affects, and the pressures and incentives likely to exacerbate such misconduct. We conclude with a discussion of how the taxonomy can help shape future good research practice (thereby setting a better example to students), and offer some propositions for future research.