The Performance Metric for Enterprise Service Bus (ESB) in SOA system: Theoretical underpinnings and empirical illustrations for information processing

Now days, the businesses are going online and e-Commerce industry is on its boom. In this changing era of development, services are to be Robust, Agile, Accessible and Available to its clients. For secured and guaranteed delivery of services, every big organization is shifting their service delivery model to Enterprise Service Bus (ESB). It promises to set up a strong guideline to build System Oriented Architecture (SOA) system, which leverages multiple services from different application domains. This paper presents an analytical survey of ESB on different parameters influencing the performance of SOA in the present changing scenario and service patterns.     

A taxonomy for moving object queries in spatial databases

In the past decade, many works have focused on the development of moving object database indexing and querying. Most of those works have concentrated on the common spatial queries which are used with static objects as well. However, moving objects have different features from static objects which may lead to a variety of queries. Therefore, it is important to understand the full spectrum of moving object queries, even before starting to build an index structure for such objects. The aim of this paper is to provide a complete picture of the capabilities of moving object queries. Thus motivated, in this paper we propose a taxonomy of moving object queries, comprising five perspectives: (i) Location perspective, (ii) Motion perspective, (iii) Object perspective, (vi) Temporal perspective and (v) Patterns perspective. These give an overall view of what moving object queries are about. In this work, each perspective is described and examples are given.     

An elementary approach to optimal discrete-time search strategies

Optimal strategies are known for the finite and infinite horizon discrete-time search with constant unit cost and without recall. These strategies were obtained in the theory of optimal stopping, based on the martingale convergence theorem and other tools from probability theory. We present here an elementary approach to these problems, relying only on routine calculation of expected values. In the finite horizon case, the solution utilizes a simple form of backward induction, in conjunction with a nonlinear dynamical system, to compute the parameters of the optimal strategy. An elementary proof is also given that a simple threshold search is optimal among all strategies with finite expected total cost.     

基于土地节约型的陕北山地聚落空间发展模式探究

陕北地区自然生态环境脆弱，加之城镇化进程的快速推进，制约了当地社会、经济、生态的协调发展。本文着眼于聚落空间可持续发展的目标，在土地节约的政策导向下，试图探索陕北山地聚落空间形态发展的适宜性模式。     

Sequential detection of three-dimensional signals under dependent noise

We study detection methods for multivariable signals under dependent noise. The main focus is on three-dimensional signals; that is, on signals in the space–time domain. Examples for such signals are multifaceted. They include geographic and climatic data as well as image data that are observed over a fixed time horizon. We assume that the signal is observed as a finite block of noisy samples whereby we are interested in detecting changes from a given reference signal. Our detector statistic is based on a sequential partial sum process, related to classical signal decomposition and reconstruction approaches applied to the sampled signal. We show that this detector process converges weakly under the no change null hypothesis that the signal coincides with the reference signal, provided that the spatial–temporal partial sum process associated with the random field of the noise terms disturbing the sampled signal converges to a Brownian motion. More generally, we also establish the limiting distribution under a wide class of local alternatives that allows for smooth as well as discontinuous changes. Our results also cover extensions to the case in which the reference signal is unknown. We conclude with an extensive simulation study of the detection algorithm.     

Geometric patterns of a recursive waltz dance

Abstract

The article concerns the explorations of the beauty of geometric patterns of recursive relative motions. Relative motions can be regarded as waltz dances, and thus generate varieties of complex and fascinated patterns. We create an applet with Macromedia Director to generate a recursive waltz, and define a specific palette to implement the coloured trajectories. It has always been a pleasure to observe various unseen forms gradually unfurling their mysterious charms. The possibilities are endless, and they call for further and deeper exploration.     

Effect of Polyelectrolyte Conditioning and Voltages on Fractionation of Macro and Trace Metals due to Sludge Electro-Dewatering

The purpose of this laboratory study was to investigate the simultaneous impacts of the electro-dewatering process on dry solids (DS) content and mobilization of metals in sewage sludge. The results suggested that the use of polyelectrolytes is necessary in mechanical pressure-driven dewatering and also in electro-dewatering. With polyelectrolyte conditioning, the DS content in the final sludge cake could be increased to 39%. Dewatering with slightly cationic polymer was not effective, but medium, strongly and very strongly cationic polymers performed equally. During electro-dewatering, an increase of voltage from 10 to 40 V resulted in a dryer sludge cake. Polyelectrolyte addition reduced the content of exchangeable metal species and increased less mobile, reducible species in the sludge. Furthermore, the more stable or immobile metal fractions were more likely to remain intact in dewatered sludge. Among heavy metals, Cu and Pb were immobile but Cr, Co, Ni, and Zn could more easily be mobilized during electro-dewatering. The application of high voltage had a direct effect on the migration of metal fractions, whereas, the sludge conditioning by a different cationic polymer had an indirect effect on the migration of these metals during electro-dewatering.     

Epidemiology of moderate-to-severe injury patterns observed in rollover crashes

BackgroundPrevious epidemiological studies have highlighted the high risk of injury to the head, thorax, and cervical spine in rollover crashes. However, such results provide limited information on whole-body injury distribution and multiple region injury patterns necessary for the improvement and prioritization of rollover-focused injury countermeasures.MethodsSampled cases representing approximately 133,000 U.S. adult occupants involved in rollover crashes (between 1995 and 2013) sustaining moderate-to-severe injuries were selected from the National Automotive Sampling System Crashworthiness Data System database. A retrospective cohort study, based on a survey of population-based data, was used to identify relevant whole body injury patterns.ResultsAmong belted occupants injured in rollover crashes, 79.2% sustained injuries to only one body region. The three most frequently injured (AIS2+) body regions were head (42.1%), upper extremity (28.0%), and thorax (27.1%). The most frequent multi-region injury pattern involved the head and upper extremity, but this pattern only accounted for 2.3% of all of occupants with moderate or worse injuries.ConclusionsThe results indicated that for rollover-dominated crashes, the frequently observed injury patterns involved isolated body regions. In contrast, multi-region injury patterns are more frequently observed in rollovers with significant planar impacts. Identification of region-specific injury patterns in pure rollover crashes is essential for clarifying injury mitigation targets and developing whole-body injury metrics specifically applicable to rollovers.     

Discovering and modeling meta-structures in human behavior from city-scale cellular data

For a long time, researchers explore spatio-temporal properties in mobility to understand human behavior. They have discovered many statistical laws about human dynamics. Unfortunately, we still have limited knowledge about the spatio-temporal structure of individuals’ movement at a large scale. In this paper, we studied the unified spatio-temporal structures (i.e., meta-structures) in human mobility. We hereby propose a meta-structure discovery algorithm by coupling both topology and spatio-temporal attributes of mobility graphs. With the construction of individual profiles from meta-structure analyses, we provided a novel mobility model from a process-driven perspective, which reduced the dependence of many existing models on the consistency between local and global mobility statistics. We gained some insights on the dominating meta-structures in human mobility by leveraging mobile data in a large city. The statistical distribution of meta-structures is found to be determined by the intrinsic heterogeneity of spatio-temporal properties in human behavior. Our model evaluation showed that a process with basic rules could demonstrate the key statistical properties in mobility meta-structures. We believe that these approaches and observations would be a good reference for management of human mobility in mobile networks and transportation systems.