互联网应建立全新的社会秩序管理体系

互联网诞生之初的作用是一个互联互通的通信工具。当时的主要管理工作都是基于安全目的,保证信息的＂可用性、完整性、保密性＂。经过20多年发展,互联网的作用、身份已经发生了巨大的变化,和现实社会密不可分,成为一个虚拟社会。而在管理互联网的理念、手段、工具等方面没有大的突破,还局限在信息安全范围内,言必谈＂安全＂。既然是＂社会＂,就必然有社会学的属性、需要用社会学的体系、手段、机制,才能管理好＂社会＂,解决社会学问题。事实也证明,用非社会学的手段来解决社会问题,是无解的!     

Field cross correlator for analysis of ultrafast signals

The cross-correlation function between two light fields is recorded with the help of a new device. The proposed correlator exhibits ultrashort time resolution. The optical path difference between the two interfering beams does not have to be known with interferometric precision. The experimental dynamic range proved to be as large as 10(5). The device features imaging capabilities that could be applied to the analysis of two-dimensional images with ultrashort time resolution.     

Joint pricing and advertising strategy with reference price effect

Consumers are susceptible to reference price effects when they make purchase decisions for a certain product. Meanwhile, the sales price and advertisement are the determinable factors that have impact on consumers’ reference price which are also fundamental marketing strategies. Therefore, how to determine an appropriate sales price and advertising effort level to maximise firms’ profits is an essential task. A joint pricing and advertising problem for a monopolistic firm with consideration of reference price effect is investigated, where consumer demand rate is price-sensitivity and depends on the gap between the sales price and the reference price in consumers’ mind. An optimisation model is established to maximise the firm’s total profit by making a joint pricing and advertising strategy. The static and dynamic joint strategies are obtained by applying Pontryagin’s maximum principle. Results show that the dynamic strategies dominate the static ones. Furthermore, the dynamic pricing and dynamic advertising strategies are strategic complements. Additionally, the length of the sales period plays a key role in determining the superiority of the two dynamic strategies. Specifically, a relatively short sales period highlights the value of the dynamic advertising while a long sales period strengthens the function of the dynamic pricing.     

TreeNetViz: revealing patterns of networks over tree structures

Network data often contain important attributes from various dimensions such as social affiliations and areas of expertise in a social network. If such attributes exhibit a tree structure, visualizing a compound graph consisting of tree and network structures becomes complicated. How to visually reveal patterns of a network over a tree has not been fully studied. In this paper, we propose a compound graph model, TreeNet, to support visualization and analysis of a network at multiple levels of aggregation over a tree. We also present a visualization design, TreeNetViz, to offer the multiscale and cross-scale exploration and interaction of a TreeNet graph. TreeNetViz uses a Radial, Space-Filling (RSF) visualization to represent the tree structure, a circle layout with novel optimization to show aggregated networks derived from TreeNet, and an edge bundling technique to reduce visual complexity. Our circular layout algorithm reduces both total edge-crossings and edge length and also considers hierarchical structure constraints and edge weight in a TreeNet graph. These experiments illustrate that the algorithm can reduce visual cluttering in TreeNet graphs. Our case study also shows that TreeNetViz has the potential to support the analysis of a compound graph by revealing multiscale and cross-scale network patterns.     

Multiplication fusion of sparse and collaborative representation for robust face recognition

Multimedia Tools and Applications - Sparse representation based classification (SRC) and collaborative representation based classification (CRC) are two well-known methods in representation-based...     

Adaptive picking of microseismic event arrival using a power spectrum envelope

An automatic, adaptive, spectrogram-based algorithm for picking the arrival time of microseismic data is proposed. The algorithm provides a significant improvement in the ratio of detected events to false triggers and in the resolution of the microseismic structure. It mainly addresses the problem of automatic picking when the signal-to-noise ratio (S/N) is low and so false and missed triggers frequently occur. It combines the short time average/long time average (STA/LTA) algorithm with an envelope algorithm. It also constructs an envelope from a time-frequency representation of the signal. The threshold is set dynamically, according to the existing noise level and the S/N ratio. The algorithm also uses the fixed LTA value to represent the noise level for a seismic record. It is applied to pick the arrival times of P-waves of local events recorded at eight stations.     

基于IMAN的产品数据管理的实现

该文首先提出了上海家化包装部对 ＰＤＭ的应用需求,在此基础上讨论了包装部 ＰＤＭ系统的功能要求、体系结构、硬件配置和开发技术。最后,根据ＰＤＭ实施的具体实践,分析了 ＰＤＭ实施的效益和障碍。     

A parallel matrix factorization based recommender by alternating stochastic gradient decent

Collaborative Filtering (CF) can be achieved by Matrix Factorization (MF) with high prediction accuracy and scalability. Most of the current MF based recommenders, however, are serial, which prevent them sharing the efficiency brought by the rapid progress in parallel programming techniques. Aiming at parallelizing the CF recommender based on Regularized Matrix Factorization (RMF), we first carry out the theoretical analysis on the parameter updating process of RMF, whereby we can figure out that the main obstacle preventing the model from parallelism is the inter-dependence between item and user features. To remove the inter-dependence among parameters, we apply the Alternating Stochastic Gradient Solver (ASGD) solver to deal with the parameter training process. On this basis, we subsequently propose the parallel RMF (P-RMF) model, of which the training process can be parallelized through simultaneously training different user/item features. Experiments on two large, real datasets illustrate that our P-RMF model can provide a faster solution to CF problem when compared to the original RMF and another parallel MF based recommender.