Properties of aqueous solutions for two binary mixed systems between two kinds of bile salts and nonionic surfactants

The micellar properties of aqueous binary mixed solutions for two systems consisting of sodium cholate (NaC)-octaoxyethylene glycol mono n-decyl ether (C₁₀E₈) and sodium glycocholate (NaGC)-C₁₀E₈ have been studied on the basis of surface tensions, polarity of the micelle interior and the mean aggregation number. Application of two theoretical treatments, based on regular solution and excess thermodynamic quantities for critical micellar concentration (CMC) data from surface tension curves of two mixed systems showed that the mole fraction of each bile salt in the mixed micelles near the CMC is lower than that of the corresponding prepared mole fraction in the mixed solution. The polarity of the interior suggested that the hydrophobicity of intramicelles increased with the increase of the mole fraction of bile salt in the mixed solution and that the mixed micelles become dramatically more hydrophobic at a mole fraction of 0.68 for NaGC−C₁₀E₈ system and 0.75 for NaC−C₁₀E₈ system, respectively. This implies that the micelles become richer in the bile salt molecules and the tendency appears strongly for NaGC−C₁₀E₈ system due to the strong cohesion between the conjugated glycines in the NaGC molecules. The decrease of aggregation number with the increase of the mole fraction of bile salts shows that the micelles approach those of the single system of each bile salt. This supports the previously mentioned facts.     

Implementation of the quadrature method of moments in CFD codes for aggregation-breakage problems

In this work the quadrature method of moments (QMOM) is implemented in a commercial computational fluid dynamics (CFD) code (FLUENT) for modeling simultaneous aggregation and breakage. Turbulent and Brownian aggregation kernels are considered in combination with different breakage kernels (power law and exponential) and various daughter distribution functions (symmetric, erosion, uniform). CFD predictions are compared with experimental data taken from other work in the literature and conclusions about CPU time required for the simulations and the advantages of this approach are drawn.     

基于PAGM模型的浇注系统对螺旋桨铸件夹渣率的影响

基于分散相粒子运动模型,考虑夹渣在随流运动过程中动态聚合长大现象,构建了夹渣聚合长大模型(PAGM,Particles Aggregation Growth Model)。采用PAGM对铝合金螺旋桨铸件浇注过程中夹渣的运动轨迹、聚合长大行为及最终位置进行了模拟计算和试验验证。在此基础上研究了浇注系统对铸件夹渣分布及夹渣率的影响。结果表明,浇注系统设计对夹渣运动行为及分布有较大影响,PAGM可有效提升对铸件夹渣分布预测的准确性,为铸件优化设计及失效分析提供参考。     

Learning to rank academic experts in the DBLP dataset

Expert finding is an information retrieval task that is concerned with the search for the most knowledgeable people with respect to a specific topic, and the search is based on documents that describe people's activities. The task involves taking a user query as input and returning a list of people who are sorted by their level of expertise with respect to the user query. Despite recent interest in the area, the current state‐of‐the‐art techniques lack in principled approaches for optimally combining different sources of evidence. This article proposes two frameworks for combining multiple estimators of expertise. These estimators are derived from textual contents, from graph‐structure of the citation patterns for the community of experts and from profile information about the experts. More specifically, this article explores the use of supervised learning to rank methods, as well as rank aggregation approaches, for combining all of the estimators of expertise. Several supervised learning algorithms, which are representative of the pointwise, pairwise and listwise approaches, were tested, and various state‐of‐the‐art data fusion techniques were also explored for the rank aggregation framework. Experiments that were performed on a dataset of academic publications from the Computer Science domain attest the adequacy of the proposed approaches.     

A dimension map for molecular aggregates

A pair of gyradius ratios, defined from the principal radii of gyration, are used to generate a dimension map that describes the geometry of molecular aggregates in water and in organic solvents. Molecular dynamics simulations were performed on the aggregation of representative biomolecules and polyaromatic compounds to demonstrate application of the dimension map. It was shown that molecular aggregate data on the dimension map were bounded by two boundary curves, and that the map could be separated into three regions representing three groups of structures: one-dimensional rod-like structures; two-dimensional planar structures or short-cylinder-like structures; and three-dimensional sphere-like structures. Examining the location of the aggregates on the dimension map and how the location changes with solvent type and solute material parameter provides a simple yet effective way to infer the aggregation manner and to study solubility and mechanism of aggregation.     

MC-MLAS: Multi-channel Minimum Latency Aggregation Scheduling in Wireless Sensor Networks

Data aggregation is a key, yet time-consuming functionality in wireless sensor networks (WSNs). Multi-channel design is a promising technique to alleviate interference as a primary reason for long latency of TDMA aggregation scheduling. Indeed, it provides more potential of parallel transmissions over different frequency channels, thus minimizing time latency. In this paper, we focus on designing a multi-channel minimum latency aggregation scheduling protocol, named MC-MLAS, using a new joint approach for tree construction, channel assignment, and transmission scheduling. To our best knowledge, this is the first work in the literature which combines orthogonal channels and partially overlapping channels to consider the total latency involved in data aggregation. Extensive simulations verify the superiority of MC-MLAS in WSNs.     

A hybrid aggregation and compression technique for road network databases

Vector data and in particular road networks are being queried, hosted and processed in many application domains such as in mobile computing. Many client systems such as PDAs would prefer to receive the query results in unrasterized format without introducing an overhead on overall system performance and result size. While several general vector data compression schemes have been studied by different communities, we propose a novel approach in vector data compression which is easily integrated within a geospatial query processing system. It uses line aggregation to reduce the number of relevant tuples and Huffman compression to achieve a multi-resolution compressed representation of a road network database. Our experiments performed on an end-to-end prototype verify that our approach exhibits fast query processing on both client and server sides as well as high compression ratio.

Fault tolerant multiple event detection in a wireless sensor network

With an increasing acceptance of Wireless Sensor Networks (WSNs), the health of individual sensor is becoming critical in identifying important events in the region of interest. One of the key challenges in detecting event in a WSN is how to detect it accurately transmitting minimum information providing sufficient details about the event. At the same time, it is also important to devise a strategy to handle multiple events occurring simultaneously. In this paper, we propose a Polynomial-based scheme that addresses these problems of Event Region Detection (PERD) by having a aggregation tree of sensor nodes. We employ a data aggregation scheme, TREG (proposed in our earlier work) to perform function approximation of the event using a multivariate polynomial regression. Only coefficients of the polynomial (P$P$) are passed instead of aggregated data. PERD includes two components: event recognition and event report with boundary detection. This can be performed for multiple simultaneously occurring events. We also identify faulty sensor(s) using the aggregation tree. Performing further mathematical operations on the calculated P$P$ can identify the maximum (max) and minimum (min) values of the sensed attribute and their locations. Therefore, if any sensor reports a data value outside the [min, max] range, it can be identified as a faulty sensor. Since PERD is implemented over a polynomial tree on a WSN in a distributed manner, it is easily scalable and computation overhead is marginal. Results reveal that event(s) can be detected by PERD with error in detection remaining almost constant achieving a percentage error within a threshold of 10%$10\%$ with increase in communication range. Results also show that a faulty sensor can be detected with an average accuracy of 94%$94\%$ and it increases with increase in node density.     

基于一致性指标的两类不确定偏好信息集结

研究了两类区间数判断矩阵偏好信息的集结问题.首先,基于Saaty提出的数字互反判断矩阵一致性检验指标(CR),给出了区间数互反判断矩阵的满意一致性条件;然后利用互反与互补判断矩阵之间的关系求解出数字互补判断矩阵的一致性指标(CGCI),并在此基础上给出了区间数互补判断矩阵的满意一致性条件;最后建立了一致性指标最大的两类区间数判断矩阵偏好信息的集结模型,并用此模型解决了供应链中伙伴企业的选择问题.     

虚拟计算环境实验床平台的设计与实现

虚拟计算环境的提出是为了克服互联网资源的"成长性、自治性和多样性"等自然特性与通过全局集中控制达到资源有效共享和综合利用的矛盾.基于虚拟计算环境的体系结构和核心概念,部署了一个真正开放性、分布式的大规模网络环境,在其上设计与实现了一个三层实验床平台系统,包括资源组织、监测、调度、安全等子系统.在平台上进行了网络信息获取实验,验证了该平台设计的科学性与合理性,从实现角度给了虚拟计算环境一个可行的参考.