山西省重点实验室评估政策研究

省重点实验室是地方科技创新平台的重要组成部分,发挥着为地方集聚人才、提升基础研究和应用基础研究能力的重要作用,重点实验室评估政策的制定和实施应以推动实验室提质增效、发挥科技创新平台效用为基础.在阐述实验室体系、评估意义及重点实验室定位、作用的基础上,结合国内外考核评估相关政策、山西省现有实验室建设情况,提出了山西省重点实验室评估政策的建议.     

De Casteljau Algorithm and Degree Elevation of Toric Surface Patches

De Casteljau algorithm and degree elevation of Bézier and NURBS curves/surfaces are two important techniques in computer aided geometric design. This paper presents the de Casteljau algorithm and degree elevation of toric surface patches, which include tensor product and triangular rational Bézier surfaces as special cases. Some representative examples of toric surface patches with common shapes are illustrated to verify these two algorithms. Moreover, the authors also apply the degree elevation of toric surface patches to isogeometric analysis. And two more examples show the effectiveness of proposed method.     

Cost and Service-Level-Based Model for a Seru Production System Formation Problem with Uncertain Demand

With increasing demand diversification and short product lifecycles, industries now encounter challenges of demand uncertainty. The Japanese seru production system has received increased attention owing to its high efficiency and flexibility. In this paper, the problem of seru production system formation under uncertain demand is researched. A multi-objective optimization model for a seru production system formation problem is developed to minimize the cost and maximize the service level of the system. The purpose of this paper is to formulate a robust production system that can respond efficiently to the stochastic demand. Sample average approximation (SAA) is used to approximate the expected objective of the stochastic programming. The non-dominated sorting genetic algorithm II (NSGA-II) is improved to solve the multi-objective optimization model. Numerical experiments are conducted to test the tradeoff between cost and service level, and how the performance of the seru production system varies with the number of product types, mean and deviation of product volume, and skill-level-based cost.     

Breeding preferences in the treefrogs Dryophytes japonicus (Hylidae) in Mongolia

ABSTRACT

When a species occurs over a broad range of climates and landscapes, the breeding ecology of that species is expected to vary locally. Additionally, a basic knowledge of breeding ecology is required before other types of studies may be conducted, such as physiology or conservation. In North East Asia, Dryophytes japonicus is distributed from Japan to Mongolia, where its breeding ecology is unknown. The objectives of this study were to understand the breeding requirements of D. japonicus in this part of its range. We collected data for Dryophytes japonicus at 56 sites located within 23 independent localities in Northern Mongolia during the breeding season 2017. The data collected included habitat type and co-occurring amphibian, fishes and bird species. Our results show that the species prefers circa 70 m long oxbow lakes for breeding, while habitat characteristics, water quality and co-occurring species were not significantly associated with the occurrence of the species. We therefore conclude that D. japonicus is behaviourally plastic in Mongolia, as it is in other portions of its range, and that the species can use several types of environments and co-occur with different species at its breeding sites. Corvus dauuricus was the only bird species significant predicting the occurrence of D. japonicus, likely because of overlapping ecological preferences.     

Attack and Defense Strategies in Complex Networks Based on Game Theory

To investigate the attack and defense strategies in complex networks, the authors propose a two-player zero-sum static game model with complete information which considers attack and defense strategies simultaneously. The authors assume that both the attacker and defender have two typical strategies: Targeted strategy and random strategy. The authors explore the Nash equilibriums of the attacker-defender game and demonstrate that when the attacker's attack resources are not so significantly abundant as the defender's resources, there exists a pure-strategy Nash equilibrium in both model networks and real-world networks, in which the defender protects the hub targets with large degrees preferentially, while the attacker prefers selecting the targets randomly. When the attack resources are much higher than defense resources, both the attacker and the defender adopt the targeted strategy in equilibriums. This paper provides a new theoretical framework for the study of attack and defense strategies in complex networks.     

融媒体环境下的受众计算:途径与挑战

融媒体改革是传统媒体应对传媒经济平台化和传媒平台智能化浪潮的一项重要措施.传统机构在融媒体环境中利用数据驱动的计算传播学方法“重新”认识受众、量化传播效果,既是时代的必然,又是时代的需要.本文论述融媒体环境中受众计算的“为什么”和“怎么做”问题,将受众分析分解为三个纵向数据维度(文本、网络和时空数据)和两个横向方法维度(统计分析和机器学习).最后,我们着重讨论融媒体受众计算所面临的困难和挑战,并提出可能的解决方案.     

新冠肺炎疫情防控对数字政府建设的影响及建议

 在新型冠状病毒肺炎疫情防控工作中，数字政府发挥了积极作用，同时疫情防控也为数据共享开放带来新动力。阐述了数字政府在科学决策、经济调节、公共服务、市场监管、社会治理等领域发挥的重要作用，梳理了疫情防控为数字政府建设带来的新空间，分析了数字政府建设面临的挑战和发展瓶颈，从加强顶层设计、加强政务数据治理、强化人才队伍建设等方面提出了发展建议。     

一种基于工作流网的游戏作弊检测系统

游戏作弊对网络游戏危害很大,目前反作弊技术的瓶颈是效率低并且过多依赖于签名匹配。提出一种高效且不依赖于签名匹配的游戏作弊检测系统,用工作流网对作弊行为建模,通过流程树对作弊行为模型进行融合,在不影响检测结果的前提下节省存储空间。用热门网游的作弊软件对系统进行实验,存储空间降低率达到约60%,证明了该系统框架是可行、有效的。     

复杂仿真系统重用模型可信度评估方法

在资源高度共享的今天,模型重用可增强仿真应用的灵活性和可扩展性,是复杂仿真系统构建的必然选择。然而,评估多模型组合仿真下的可信性是模型能否实现有效重用的基本问题。针对面向实物和面向数值解算两个不同应用环境的仿真模型重用,提出基于偏差传播的仿真重用模型可信度评估方法,详细介绍了各自建模方式及评估方法。以无人机复杂仿真系统为例,通过与经典可信度评估方法对比,说明了该方法可降低在重用模型可信度方面的评估难度,验证了方法的可行性。     

Efficient Feature Extraction Using Apache Spark for Network Behavior Anomaly Detection

Extracting and analyzing network traffic feature is fundamental in the design and implementation of network behavior anomaly detection methods. The traditional network traffic feature method focuses on the statistical features of traffic volume. However, this approach is not sufficient to reflect the communication pattern features. A different approach is required to detect anomalous behaviors that do not exhibit traffic volume changes,such as low-intensity anomalous behaviors caused by Denial of Service/Distributed Denial of Service(Do S/DDo S)attacks, Internet worms and scanning, and Bot Nets. We propose an efficient traffic feature extraction architecture based on our proposed approach, which combines the benefit of traffic volume features and network communication pattern features. This method can detect low-intensity anomalous network behaviors and conventional traffic volume anomalies. We implemented our approach on Spark Streaming and validated our feature set using labelled real-world dataset collected from the Sichuan University campus network. Our results demonstrate that the traffic feature extraction approach is efficient in detecting both traffic variations and communication structure changes.Based on our evaluation of the MIT-DRAPA dataset, the same detection approach utilizes traffic volume features with detection precision of 82.3% and communication pattern features with detection precision of 89.9%. Our proposed feature set improves precision by 94%.