Solving linear generalized Nash equilibrium problems numerically

This paper considers the numerical solution of linear generalized Nash equilibrium problems (LGNEPs). Since many methods for nonlinear problems require the nonsingularity of some second-order derivative, standard convergence conditions are not satisfied in our linear case. We provide new convergence criteria for a potential reduction algorithm (PRA) that allow its application to LGNEPs. Furthermore, we discuss a projected subgradient method (PSM) and a penalty method that exploit some known Nikaido–Isoda function-based constrained and unconstrained optimization reformulations of the LGNEP. Moreover, it is shown that normalized Nash equilibria of an LGNEP can be obtained by solving a single linear program. All proposed algorithms are tested on randomly generated instances of economic market models that are introduced and analysed in this paper and that lead to LGNEPs with shared and with non-shared constraints. It is shown that these problems have some favourable properties that can be exploited to obtain their solutions. With the PRA and in particular with the PSM we are able to compute solutions with satisfying precision even for problems with up 10,000 variables.     

Assessment of crowdsourcing and gamification loss in user-assisted object segmentation

There has been a growing interest in applying human computation – particularly crowdsourcing techniques – to assist in the solution of multimedia, image processing, and computer vision problems which are still too difficult to solve using fully automatic algorithms, and yet relatively easy for humans. In this paper we focus on a specific problem – object segmentation within color images – and compare different solutions which combine color image segmentation algorithms with human efforts, either in the form of an explicit interactive segmentation task or through an implicit collection of valuable human traces with a game. We use Click’n’Cut, a friendly, web-based, interactive segmentation tool that allows segmentation tasks to be assigned to many users, and Ask’nSeek, a game with a purpose designed for object detection and segmentation. The two main contributions of this paper are: (i) We use the results of Click’n’Cut campaigns with different groups of users to examine and quantify the crowdsourcing loss incurred when an interactive segmentation task is assigned to paid crowd-workers, comparing their results to the ones obtained when computer vision experts are asked to perform the same tasks. (ii) Since interactive segmentation tasks are inherently tedious and prone to fatigue, we compare the quality of the results obtained with Click’n’Cut with the ones obtained using a (fun, interactive, and potentially less tedious) game designed for the same purpose. We call this contribution the assessment of the gamification loss, since it refers to how much quality of segmentation results may be lost when we switch to a game-based approach to the same task. We demonstrate that the crowdsourcing loss is significant when using all the data points from workers, but decreases substantially (and becomes comparable to the quality of expert users performing similar tasks) after performing a modest amount of data analysis and filtering out of users whose data are clearly not useful. We also show that – on the other hand – the gamification loss is significantly more severe: the quality of the results drops roughly by half when switching from a focused (yet tedious) task to a more fun and relaxed game environment.     

Confirmation Bias in Online Searches: Impacts of Selective Exposure Before an Election on Political Attitude Strength and Shifts

Impacts of Internet use on political information seeking and subsequent processes have been subject to much debate. A 2‐session online field study presented online search results on political topics to examine selective exposure and its attitudinal impacts. Session 1 captured attitudes, including their accessibility. Session 2 tracked what online search results participants selected and how long they read them; participants then reported attitudes again. The study represented a 4x8x2x2 within‐subjects design: 4 topics, 8 browsing intervals each, with articles presenting opposing stances, with low versus high source credibility. Attitude‐consistent messages and messages from high‐credibility sources were preferred. Exposure to attitude‐consistent search results increased attitude accessibility and reinforced attitudes, whereas exposure to attitude‐discrepant content had opposite effects, regardless of messages' source credibility.     

一种SaaS模式防空作战仿真想定编辑系统实现

针对目前仿真想定编辑系统在通用性、灵活性以及更新升级等方面存在的问题,设计了一种SaaS(Software-as-a-service)模式的防空作战仿真想定编辑系统。通过为防空武器建立统一的数据模型(数据类集)实现数据处理的独立性;通过设计与具体武器独立的想定编辑相关的业务逻辑模块,实现业务逻辑的相对独立性;利用MapXtreme Java智能多线程机制解决多用户的并发编辑问题。另外,将系统部署在云计算基础设施平台上,解决了传统C/S模式系统与平台相关联、更新升级困难等缺点,也提升了系统的使用灵活性和用户体验。最后通过实例验证了系统的科学性和有效性。     

黑河水库引水洞上部滑坡的稳定性数值模拟分析

以黑河引水洞上部滑坡为例,采用二维离散元软件对滑坡的变形过程进行了数值模拟,分别从应力、应变、塑性区分布等方面分析滑坡的变形特征,并对坡面一点的速率、位移情况进行监测,模拟结果与实际观测结果大体上是吻合的,离散元数值模拟在一定程度上反映了坡体变形破坏的总体趋势.     

“信息论与编码”双语教学课程建设与实践

近年来,随着信息技术的飞速发展和对外交流的日益频繁,我校和中国其他高校一样在双语教学方面做了一系列的探索与实践。文章就我校开展的《信息论与编码》双语教学课程的特点,提出了在本科教学中的双语教学课程建设与教学改革方案并在教学中取得了良好的效果,具有一定的借鉴意义。     

植物标本数据库系统发展研究

研究目前常见的单机版系统、C/S模式、B/S模式、分布式网络数据库系统和地理信息系统,并对其优缺点进行了分析,对未来发展趋势进行了展望.     

贸易地图生成软件并行处理方案的研究与实现

本文通过分析贸易地图生成软件的主要特征,找出软件运行的性能瓶颈,在此基础上制定了适合该系统的基于参数扫描分析的并行处理方案,并且在集群运行平台上实现了这一并行处理方案.系统运行结果证实,该方案缩短了生成贸易地图的时间,改善了系统的整体性能.     

基于可再分发抗合谋编码的低失真水印方案

在大数据的时代背景下,数据潜在的价值使其成为重要的财富之一。数据的非法篡改、修正和非法分发给追踪数据的泄密源头带来巨大挑战。数字指纹技术可应用在数据泄密溯源领域,即在数据中嵌入一串能够唯一标识用户信息的序列,当数据发生泄密后,提取其中蕴含的数字指纹,追踪到泄密的叛逆者。多个用户对数据合谋攻击并泄密数据,从而毁坏其中嵌入的指纹信息达到逃脱追责的目的,抗合谋编码能够解决此问题。针对现有的数字指纹编码无法满足数据再分发需求、数字指纹嵌入造成较大数据失真的问题,本文使用BIBD（Balanced incomplete block design）作为外码,码字扩展后的C码作为内码,构建一种可再分发的抗合谋指纹编码RD-ACC（Redistributable anti-collusion fingerprint coding）。在此基础上,提出一种基于多目标优化的数据库指纹算法,能够在较小的数据库失真情况下保证数字指纹较高的鲁棒性,提取出的RD-ACC能够有效抵抗组内、组间多用户合谋攻击。实验结果表明,该算法能够在较小的数据失真下实现数据的再分发操作,并且能抵抗合谋攻击进行泄密溯源。