一种关注消息时效性的机会社会网络中节点传播能力分析模型

当前评估节点传播能力的工作大多针对静态网络.本文采用演化图模型对机会社会网络进行刻画,通过将传统通路(walk)的概念和静态图中的Katz中心性度量扩展到动态网络中,提出了一种基于历史相遇记录评估节点消息分发能力的方法.进一步,针对消息的时效性特性,本文提出了消息随时间推移效用递减的节点传播能力分析模型,该模型考虑了消息所有可能经历的空间和时间通路,并沿时间方向向下加权以描述消息时效性递减效应,可用于有效计算和预测节点的消息转发能力.本文的结论通过真实数据得到了验证.     

Design of new quadruplexer with compact size,high isolation and wide stopband

This study presents a quadruplexer (1.8/2.4/3.5/5.8 GHz) with compact size, high isolation, low insertion loss and wide stopband based on the multi-mode resonators. The quadruplexer is composed of four pairs of coupled multi-mode resonators (uniform impedance resonator, UIR and stepped impedance resonators, SIRs) and the source–load coupling lines. Each channel (passband) can be easily determined by tuning the impedance ratio (K) and length ratio (α) of the SIRs so as to implement a 2-order bandpass filter individually. The source–load coupling lines are designed to correspond to the quarter-wavelength of the center frequency at each channel. The proposed quadruplexer shows a simple configuration, an effective design method and a small circuit size.     

Transconductance improvement method for low-voltage bulk-driven input stage

A proposed transconductance enhanced method for low-voltage bulk-driven input stage is presented in this paper. The basic idea is to use current–shunt auxiliary amplifier to improve the voltage gain from the inputs to the gates of bulk-driven pairs. The enhanced voltage gain of the auxiliary amplifier leads to the improvement of the effective transconductance of the input stage. Results show that the transconductance of the OTA using the proposed bulk-driven input stage improves almost 200% without additional power and area dissipation compared to the conventional bulk-driven counterpart.     

A design space exploration methodology for customizing on-chip communication architectures: Towards fractal NoCs

Recent studies have shown that On-Chip Interconnects (OCI) architecture represents one of the most important component that determines the overall performance of future System-on-Chip (SoC). In order to improve the performance of a specific SoC application domain, the OCI architecture must be optimized at design/run time. Different OCI-based architectures have been recently proposed, the most recent ones are fractal-based or self-similar topologies. In this paper, we present a customization approach by adding strategic links targeted to match large application workload. Simulations results show the effectiveness of this method to achieve better performance compared to the basic OCI architectures. Furthermore, fractal based OCIs perform well almost in all traffic patterns because of their attractive properties.     

Understanding mobile technology-fit behaviors outside the classroom

An increase in mobile device usage among college students has been documented in different countries. We provide a solid theoretical and empirical foundation for mobile learning in the context of distance education, and more guidance in terms of how to utilize emerging mobile technologies and to integrate them into their teaching more effectively. This research focuses on a deeper understanding of how learners use mobiles as learning tools outside the classroom. Our results are based on a specific population drawn from two different countries, in which the US (United States) population reflected students from the education field, while the students from Israel are drawn more from the engineering and science fields. The findings of this study contribute to the generalizations to the education field and information system designers who need to analyze and design mobile-learning (m-learning) applications to be used outside the classroom.     

Evaluation of methods for estimating aquifer hydraulic parameters

An accurate estimation of aquifer hydraulic parameters is required for groundwater modeling and proper management of vital groundwater resources. In situ measurements of aquifer hydraulic parameters are expensive and difficult. Traditionally, these parameters have been estimated by graphical methods that are approximate and time-consuming. As a result, nonlinear programming (NLP) techniques have been used extensively to estimate them. Despite the outperformance of NLP approaches over graphical methods, they tend to converge to local minima and typically suffer from a convergence problem. In this study, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) methods are used to identify hydraulic parameters (i.e., storage coefficient, hydraulic conductivity, transmissivity, specific yield, and leakage factor) of three types of aquifers namely, confined, unconfined, and leaky from real time–drawdown pumping test data. The performance of GA and ACO is also compared with that of graphical and NLP techniques. The results show that both GA and ACO are efficient, robust, and reliable for estimating various aquifer hydraulic parameters from the time–drawdown data and perform better than the graphical and NLP techniques. The outcomes also indicate that the accuracy of GA and ACO is comparable. Comparing the running time of various utilized methods illustrates that ACO converges to the optimal solution faster than other techniques, while the graphical method has the highest running time.     

Correcting geometric deviations of CNC Machine-Tools: An approach with Artificial Neural Networks

This paper presents an experimental methodology of Design for Manufacturing (DFM) used for survey and analysis of geometric deviations of CNC Machine-Tools, through their final product. These deviations generate direct costs that can be avoided through the use of Intelligent Manufacturing Systems (IMS), by the application of Artificial Neural Networks (ANNs) to predict the fabrication parameters. Finally, after the experiments, it was possible to evaluate the experimental methodology used, the equations, the variables of data adjustment and thus enable the validation of the methodology used as a tool for DFM with high potential return on product quality, development time and reliability of the process with wide application in various CNC Machines.     

Group-based Parallel Multi-scheduler for Grid computing

The Group-based Parallel Multi-scheduler (GPMS), introduced in this paper, is aimed at effectively exploiting the benefits of multicore systems for Grid scheduling by splitting jobs and machines into paired groups and independently scheduling jobs in parallel from those groups. We implemented two job grouping methods; Execution Time Balanced (ETB) and Execution Time Sorted then Balanced (ETSB), and two machine grouping methods,; Evenly Distributed (EvenDist) and Similar Together (SimTog). For each method, we varied the number of groups between 2, 4, 8 and 16. We then executed the MinMin Grid scheduling algorithm independently within the groups. We demonstrated that by sharing jobs and machines into groups before scheduling, the computation time for the scheduling process drastically improved by magnitudes of 85% over the ordinary MinMin algorithm when implemented on a HPC system. We also found that our balanced group based approach achieved better results than our previous Priority based grouping approach.     

蝶形半导体激光器恒流驱动设计与实现

蝶形半导体激光器驱动电流的稳定性直接决定了其输出波长的稳定性,进而影响检测精度。为了满足气体浓度检测中对激光器输出波长稳定可调的要求,设计了数字与模拟电路混合的恒流驱动电路。以STC90C51为主控芯片数控模块完成扫描键盘、DA转换;模拟电路主要由负反馈运算放大、高精度CMOS管和反馈电阻构成,完成电压到电流的转换,输出至蝶形半导体激光器,实现蝶形半导体激光器恒流驱动。输出电流在0~300 mA范围内连续可调,输出驱动电流误差小于±0.003 mA,满足系统对恒流驱动±0.005 mA的误差精度要求。     

食用油储存期品质变化的太赫兹光谱无损识别

为研究食用油在储存期间的品质变化情况,利用太赫兹衰减全反射技术对不同氧化程度的食用油进行无损识别.首先探究储存条件对食用油品质的影响情况,进一步根据国家定义食用油品质的标准将样品分为新鲜油、可食用油和不宜食用油,采集各类油品的太赫兹时域光谱,经数据预处理后采用欧氏距离匹配法进行聚类分析,并采用线性判别分析法进行样本分类...