Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Encodings for Web Service Messages

A major drawback of using SOAP for application integration is its enormous demand for network bandwidth. Compared to classical approaches like Java-RMI and Corba, SOAP messages typically cause more than three times more network traffic. In this chapter we will explore compression strategies and give a detailed survey and evaluation of state-of-the-art binary encoding techniques for SOAP. We also introduce a new experimental concept for SOAP compression based on differential encoding, which makes use of the commonly available WSDL description of a SOAP Web service. We not only conduct a detailed evaluation of compression effectiveness, but also provide the results of execution time measurements. Werner, Buschmann, & Fischer Copyright © 2008, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Introduction Like all other XML protocols, SOAP suffers from the fact that only a very small part of the transmitted message contains real payload. The rest of it is XML markup and protocol overhead. Comparisons on different approaches for realizing remote procedure calls (RPCs) have shown that SOAP over HTTP uses significantly more bandwidth than competitive technologies (Tian, Voigt, Naumowicz, Ritter, & Schiller, 2003; Marahrens, 2003). For our experiments, we implemented a simple RPC server and client on different platforms (MS .Net, Apache Axis, Corba, Java-RMI, RMIIIOP). Then we measured the resulting network traffic for each case using the Ethereal network analyzing utility. Figure 1 summarizes the results. For all implementations the number of transmitted bytes increases with the number of transmitted RPC messages in an almost linear way (all values do not include overhead for protocols on network layer and below). There is virtually no difference in the number of transmitted bytes between Microsoft’s SOAP Implementation and Apache Axis. Both cause more than three times more network traffic than Java-RMI and Corba. For the case of only one message (n = 1), the SOAP Implementations cause the smallest amount of traffic: 1,972 bytes (Java), 1,976 bytes (SOAP .Net), 2,626 Figure 1. Transmission of random strings (l = 250 bytes) 20 more pages are available in the full version of this document, which may be purchased using the "Add to Cart" button on the product's webpage: www.igi-global.com/chapter/efficient-encodings-web-servicemessages/31208? camid=4v1 This title is available in InfoSci-Books, InfoSci-Multimedia Technologies, Semantic Web and Web Services, BusinessTechnology-Solution, Science, Engineering, and Information Technology, InfoSci-Computer Science and Information Technology. Recommend this product to your librarian: www.igi-global.com/e-resources/library-recommendation/? id=1
Fidelity Performance of Three Filters for High Quality NDVI Time-series Analysis

Some noises still exist in standard MODIS NDVI product and need to be screened before further applications.An ideal filter should only remove noisy data,and keep the good data as much as possible.Most previous studies only concerned about the filter's performance in terms of handling noisy data,and neglected filter's capacity to retain the original high-quality data(fidelity). The present study analyzed three filters included in Timesat 2.3 tools,examined the effect of data quality on the performance of three filter algorithms,both qualitatively and quantitatively.Through comparative analysis,we concluded that Asymmetric Gaussians has the highest fidelity performance of all,followed by Double Logistic algorithm,and Savizky-Glolay algorithm performance worst.
Implementation of Map Service on Java Mobile Phone

Key aspects in realizing the maximum potential of advanced Location-Based Services (LBS) are the standardization and cross-platform availability of an Application Programming Interface (API) for mobile phones that allows access to real-time location information. This article's main goals are to em- phasize the importance of such an API and to describe the Location API for Java 2 Micro Edition (J2ME). This description includes the main features of the current "JSR179-Location API v1.0" as well as the sig- nificant enhancements. This thesis presents implementation of mobile an overall solution to the design and information service system on mobile devices.
Multi‐site rainfall simulation at tropical regions: a comparison of three types of generators

Rainfall modelling is an essential component of different hydrological studies. However, rainfall modelling in tropical regions, especially urban areas, remains inadequate. To determine the applicability of different types of rainfall modelling approaches, simulations by two Markov models (Matlab‐based weather generator (MulGETS) and multi‐site rainfall simulator (MRS)) and a Neyman–Scott based Poisson cluster model (RainSim) were compared with a proposed modified k‐nearest neighbour (KNN) model for 30 years rainfall in Singapore. The MRS model was determined to be suitable for single‐site applications in tropical regions. However, for multi‐site conditions, RainSim was adjudged the most suitable given its accuracy in preserving observed spatial information, despite its performance lagging in few statistical indicators. The KNN model was found to perform satisfactorily during the wet seasons, and was the only model that could repeat the extreme precipitation values closely. Although typical studies evaluate the performance of models based on a set of criteria, there exists a lacuna in understanding the quality of simulations by these models. Therefore, uncertainty analysis based on two different criteria was implemented to understand the performance of the stochastic processes within. Although the MulGETS model exhibited the lowest differences between Prediction Intervals, RainSim's Prediction Intervals were found to subsume observed data more often. The proposed study would be useful for users examining rainfall models for differing objectives.
An Examination of Internet Effectiveness for Non-work Activities

The Internet is frequently used for non-work activities. When used for these purposes, the effectiveness of the Internet in accomplishing these leisure activities becomes an important consideration. Research literature has remained relatively silent in regards to the examination of accomplishing non-work tasks through the Internet. This study uses Davis’ Technology Acceptance Model (TAM) as a basis to predict different types of common user web activities—entertainment, communicating, and information searching. Using Structured Equation Modeling, this paper examines the effectiveness of the Internet in accomplishing non-work activities. In this study, the overall analysis of the survey data suggests that perceived ease of use and perceived usefulness predict all three types of Internet activities. The findings of this study suggest a refinement for constructs in web usage studies and contribute to the expanding of TAM to predict perceived effectiveness of Internet usage.
Energy-efficient Communication in Ad Hoc Wireless Local Area Networks

Today there is a widespread utilization of wireless in computation, communication and control. A very popular wireless technology, belonging to the class of local area networks, is IEEE 802.11. Developed in the eighties and specified in its raw form by the IEEE in 1995, it offers comparatively high data rates and competitive ease of use. The main application scenario is the provision of Internet access for (mobile) end systems. Despite a powersaving function IEEE 802.11 network interfaces still consume a vast amount of the overall energy budget of a self-sustained end system. Hence, further efforts are necessary to reduce the energy demand of an IEEE 802.11 network interface. In this thesis several aspects of energy consumption and efficient utilization of limited energy resources of IEEE 802.11 communication systems are explored regarding the Media Access Control protocol. The investigation is based on power consumption measurements of an IEEE 802.11 network interface. These measurements provide parameters for several simulations, which are used to determine the energy consumption of the network interface for various operation modes and different radio link qualities. A new metric, the energy consumed to transmit one payload bit successfully, is employed to determine power consumption meaningfully. The results also reveal that the IEEE 802.11 power-saving creates an On/Off discharge pattern resulting in a pulsed battery discharge. Pulsed battery discharge significantly extends battery life compared to continuous discharge. Furthermore, the relation of the size of a transmitted packet to the energy consumption is analyzed. It is shown that a packet size dependent power control scheme leads to considerable energy savings. Power control is also considered from the network perspective. The particular question, whether power control reduces
Introduction To Microwave Theory

Thank you for downloading introduction to microwave theory. As you may know, people have look numerous times for their chosen readings like this introduction to microwave theory, but end up in infectious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they juggled with some harmful bugs inside their desktop computer. introduction to microwave theory is available in our digital library an online access to it is set as public so you can get it instantly. Our digital library hosts in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the introduction to microwave theory is universally compatible with any devices to read.
Cloud Computing, Contractibility, and Network Architecture

The emergence of the cloud is heightening the demands on the network in terms of bandwidth, ubiquity, reliability, latency, and route control. Unfortunately, the current architecture was not designed to offer full support for all of these services or to permit money to flow through it. Instead of modifying or adding specific services, the architecture could redesigned to make Internet services contractible by making the relevant information associated with these services both observable and verifiable. Indeed, several on-going research programs are exploring such strategies, including the NSF’s NEBULA, eXpressive Internet Architecture (XIA), ChoiceNet, and the IEEE’s Intercloud projects.
Application Study of Activity-based-accounting Method on the Items of MRI and CT Cost Calculating

Objective:To build indirect cost allocation model based on activity-based- accounting method and explore calculation for the item and disease cost,which will provide methodological guidance for payment reform.Methods:Taking items of MRI and CT in radiology department as cost object,and building the model on the base of activity chain,cost pool and cost driver.Results:Average cost and the comparison of MRI and CT between activity- based-accounting method and traditional method can be derived.Conclusion: There are wide application prospects for cost calculation of medical service.
Estimation of sub-epidemic dynamics by means of Sequential Monte Carlo Approximate Bayesian Computation: an application to the Swiss HIV Cohort Study

Our ability to accurately infer transmission patterns of infectious diseases is critical to monitor both their spread and the efficacy of public health policies. The use of phylogenetic methods for the reconstruction of viral ancestral relationships has garnered increasing interest, particularly in the characterization of HIV epidemics and sub-epidemics. In the case of this virus, the Swiss HIV Cohort Study (SHCS) contains a wide breadth of genomic data that have been widely used as a means of applying such methods. However, current approaches for quantifying the epidemiological dynamics of diseases are computationally intensive, and fail to scale well with this magnitude of data. To address this issue, we re-implement an Approximate Bayesian Computation (ABC) approach based on sequential Monte Carlo (SMC). By means of simulations, we demonstrate that our implementation is capable of inferring key epidemiological parameters of the Swiss HIV epidemic accurately, and that sampling intensity has no significant effect on the accuracy of our estimates. Applied to a subset of HIV sequences from the SHCS, we show that we can distinguish sub-epidemics that are circulating in culturally distinct Swiss regions. Given these findings, we propose that ABC-SMC samplers will allow us to evaluate the impact of new public health policies, such as the implementation of a needle exchange program in the case of HIV, based on genetic data sampled before and after the implementation of a new policy.
Plan recognition method based on intelligent planning

Based on the basic ideas of robots'action planning in the fields of intelligent planning,a plan recognition solving process by using intelligent planning was proposed.The concept of sustain degree was used to describe the uncertain relationship among the multi-agents,and the ideas of target classification was utilized to describe the cooperative relationship among the actions of multi-agent in plan recognition system.In addition,an example was introduced to explain the process of plan recognition based on planning inference,which shows the feasibility of using the planning method to solve the problems of plan recognition.
Joint Dynamic Online Social Network Analytics Using Network, Content and User Characteristics

Online social networks (OSNs) allow Internet users all over the globe to share information, exchange thoughts, and work collaboratively. Not only do OSNs provide a channel of broadcasting real-world events as they unfold, they also enable a convenient way for users to exchange experience and opinions. Understanding the relation among network topology, users, content, and their dynamics can have a significant impact both from a theoretical standpoint as well as from a practical one, for instance, to understand online user behaviors and predict future online activities. In this dissertation, I study the interplay of three important factors that encode most of the OSN dynamics: network structure, user-generated content, and user characteristics. We first present our broader contribution to computer science: the development of two novel graph algorithms for community detection and structural role detection, which are scalable to handle networks containing millions of nodes and edges. Both community and role assignments of nodes generate novel clusterings of OSN users and provide valuable insights into OSN activities, but they are often implicit or even unknown to OSN analysts. We bridge this chasm by designing algorithms that can automatically infer community and role information in large-scale OSN data. Our algorithms are (1) robust in the presence of noise in real-world data, and (2) efficient in processing large network datasets. A key element to both of these contributions is a practical approach for network sparsification which enables efficient
Integrated Parallel Data Extraction from Comparable Corpora for Statistical Machine Translation

Machine translation (MT), as a high level application of natural language processing (NLP), is a powerful tool to improve the efficiency and reduce the cost of translation. Over the last decade or two, statistical machine translation (SMT) has been the main approach in both the research community and the commercial sector. In SMT, translation knowledge is automatically acquired from parallel corpora (sentence-aligned bilingual texts), making the rapid development of MT systems for different language pairs and domains possible once parallel corpora are available. Because of the high dependence on parallel corpora, the quality and quantity of parallel corpora are crucial for SMT. However, except for a few language pairs and some specialized domains, high quality parallel corpora of sufficient size remain a scarce resource. This scarceness of parallel corpora has become the main bottleneck for SMT. Comparable corpora are a set of monolingual corpora that describe roughly the same topic in different languages, but are not exact translation equivalents of each other. Exploiting comparable corpora for SMT is the key to addressing the scarceness of parallel corpora. The reason for this is that comparable corpora are far more available than parallel corpora, and there is a large amount of parallel data contained in the comparable texts. The main focus of this thesis is extracting the parallel data from comparable corpora to improve SMT. There are three types of parallel data in comparable corpora: bilingual lexicons, parallel sentences and parallel fragments. In this thesis, we propose novel approaches to extract these three types of parallel data from comparable corpora in an integrated framework. In addition, we exploit linguistic knowledge of common Chinese characters for Chinese-Japanese parallel data extraction as a case study. Bilingual lexicon
A New FPGA Based Timing System at ELSA

At the electron stretcher facility ELSA a beam intensity upgrade from 20 mA to 200 mA is in progress. Investigations showed, that the maximum beam current is currently limited by excitation of beam instabilities. For separated characterization of single bunch instabilities from multi-bunch ones, a high beam current stored in a single revolving bunch is required. These high beam currents can only be achieved by accumulation of many shots from the injector. The existing timing system is not capable of single bunch injection and accumulation in the main stretcher ring. Therefore a new FPGA based timing system, synchronized to the RF system of the accelerator, has been developed which will completely supersede the existing one. Simultaneously the “slow” timing system, providing trigger signals for the typically 6 s long accelerator cycle, is also modernized using a similar FPGA based solution to achieve a much better duty cycle during standard operation. In this contribution the FPGA designs laying the focus on the single bunch accumulation will be presented.
A Two Stage Classification Model for Call Center Purchase Prediction

In call center [1] product recommendation field, call center as an organization between users and telecom operator, doesn’t have permission to access users specific information and the detailed products information. Accordingly, rule-based selection method is common used to predict user purchase behavior by the call center. Unfortunately, rule-based approach not only ignores the user’s previous behavior information entirely, and it is difficult to make use of the existing interaction records between users and products. Consequently, it will not get desired results if we just use the basic selection method to predict user purchase behavior directly, because the problem is that the features straightly extracted from the interaction data records are limited. In order to solve the problem above, this paper proposes a two-stage algorithm that based on K-Means Clustering Algorithm [2] and SVM [3, 4] Classification Algorithm. Firstly, we get the potential category information of products by K-Means Clustering Algorithm, then use SVM Classification Model to predict users purchasing behavior. This two-stage prediction model not only solves the feature shortage problem, but also gives full consideration to the potential features between users and product categories, which can help us to gain significant performance in call center product recommendation field.
A Novel Super-Peer Based Trust Model for Peer-to-Peer Networks

A super-peer based trust model for Peer-to-Peer(P2P)networks is presented in this paper to solve the problems of not sufficiently building trust relation between peers due to the difference of peers' interests and low probability of repeated transactions between them.In the model peers gather in a group according to their interest similarity.Trust relation is categorized into three kinds and subsequently each solution for these kinds is also put forward.Moreover,a feedback filtering algorithm based on peers' similarity is proposed to effectively filter the fake,misleading and unfair feedbacks in the referrals.Subsequent experimental results show that the proposed model is not only robust on trust security,but also has low costs and failure rate when resource search happens.
Pedestrian navigation algorithm based on the smart phone MARG sensors

The demand for navigating a user with a hand-held device,especially in GPS denied environments,has tremendously increased over the last five years. Based on this,this paper presented pedestrian navigation algorithm based on smart phone magnetic,angular rate and gravity( MARG) sensors,which is on the basis of pedestrian dead reckoning algorithm,using a low-pass filter filtered accelerometer data to detect pedestrian step,using an empirical model to estimate the pedestrian step length,and we designed an extended Kalman filter,using adaptive way to adjust timely measurement noise covariance matrix,to fuse the MARG sensor data and to estimate the optimal heading angle. Validation tests on the smart phone platform,and experimental results show that the non-magnetic or magnetic interference environment,pedestrian navigation proposed algorithm can ensure accurate,reliable,continuous location information.
Female Inventors and Inventions

Has the increase in female medical researchers led to more medical advances for women? In this paper, we investigate if the gender of inventors shapes their types of inventions. Using data on the universe of US biomedical patents, we find that patents with women inventors are significantly more likely to focus on female diseases and conditions. Consistent with the idea of women researchers choosing to innovate for women, we find stronger effects when the lead inventor on the patent is a woman. Women-led research teams are 26 percent more likely to focus on female health outcomes. This link between the gender focus of the scientist and the type of invention, in combination with the rise of women inventors, appears to have influenced the direction of innovation over the last four decades. Our findings suggest that the demography of inventors matters not just for who invents but also for what is invented.
LIDAR-based 3D Object Perception

This paper describes a LIDAR-based perception system for ground robot mobility, consisting of 3D object detection, classification and tracking. The presented system was demonstrated on-board our autonomous ground vehicle MuCAR-3, enabling it to safely navigate in urban traffic-like scenarios as well as in off-road convoy scenarios. The efficiency of our approach stems from the unique combination of 2D and 3D data processing techniques. Whereas fast segmentation of point clouds into objects is done in a 2 1 2 D occupancy grid, classifying the objects is done on raw 3D point clouds. For fast switching of domains, the occupancy grid is enhanced to act like a hash table for retrieval of 3D points. In contrast to most existing work on 3D point cloud classification, where realtime operation is often impossible, this combination allows our system to perform in real-time at 0.1s frame-rate.
Construction of the Uncertainty in the Complicated Electromagnetic Environment Simulation

Construction of the Uncertainty Space is the premiss of using exploratory analysis method in the simulation. Present the application paradigm of the exploratory analysis,analyse the Uncertainty of the Complicated Electromagnetic Environment by Shannon Entropy. From this view,make a conclusion that:the Uncertainty of the Complicated Electromagnetic Environment is caused by the parametric uncertainties,and constructing the Shannon Entropy based parametric uncertainties can build up the the Uncertainty of the Complicated Electromagnetic Environment.