Remote Web Services Research Articles

Dynamicity of Web Services and Web Scrapping

This research focuses on dynamic Web service link searching using web scraping (WS). WS is method of extracting required contents from search engine results. The proposed system inputs the functional word to search engine and retrieves required Web services from search engine results. WS method retrieves the links of the Web Service Definition Language from which service and operation elements are extracted and processed to check suitability of Web services. Matched Web services will be clustered and invoked. This research is implemented using J2EE and remote Web services are executed according to user requirement. Analysis of results justified that this will be a suitable search method to search for remote Web services and to execute using open source software.

Deadline Verification for Web Services Using Timed Automata

Many computation tasks are made today on remote cloud platforms using web services. Beyond the advantages provided by such services, many new challenges arise. One of the challenging problems is ensuring that web services respect critical deadlines. This is a critical issue, especially for real-time systems that use remote web services. This paper aims to propose a framework for deadline verification using Timed Automata (TA).

The methods for processing and storage of data in global navigation satellite systems for the task of perimeter protection

The methods for processing and storage of GNSS data for the task of perimeter protection are described. The article proposes a basic algorithm for the operation of a GNSS data collection, processing and storage system that allows you to track processed GNSS data on a remote web service in public formats, as well as send signals through a client mobile application to available platforms and systems about temporarily suspending or canceling GNSS data recording.

Systematic and Meaningful Keyword Finding Over Encipher Data in Steam

Cloud computer has actually created a great deal of interest within the evaluation area over the last few years for its several blessings, nevertheless has but also raise security and also privacy concerns. The storage and gain access to of personal documents are recognized collectively of the main problems within the area. particularly, numerous scientists explored services to examine encrypted records continue remote cloud web servers. whereas numerous schemes are planned to perform conjunctive key words search, much less interest has been kept in mind on extra specialist keeping an eye out methods. throughout this paper, we tend to gift an expression search strategy supported Blossom filters that's significantly quicker than existing options, with comparable or higher storage as well as interaction cost. Our technique makes use of a series of n-gram filters to support the practicality. The style exhibits a trade-off between storage space and also false positive rate and also is filmable to resist inclusion-relation attacks. A design method sustained associate application's target incorrect positive price is additionally stood for.

An Evaluation of Cross-Platform Frameworks for Multimedia Mobile Applications Development

Cross-Platform Mobile Development Tools allows developers to write a unique base code and create the same application for multiple mobile platforms (e.g., Android and iOS). A variety of frameworks have been proposed to support cross-platform mobile application development. PhoneGap, Sencha Touch, and Titanium are well-known frameworks designed for this purpose. The main goal of this research is to analyze their current state of maturity. In that direction, an application was developed in PhoneGap, Titanium, and Sencha, as well as native versions for Android and iOS were implemented. Such mobile application obtain information from sensors, uses camera to take pictures, applies image filters, and establishes connection to a remote Web Service. We analyzed the feasibility to build this kind of mobile application, the performance of each version, and the development effort. With our results, we intend to provide an overview of the qualities and limitations of these frameworks.

Analyzing Android Encrypted Network Traffic to Identify User Actions

Mobile devices can be maliciously exploited to violate the privacy of people. In most attack scenarios, the adversary takes the local or remote control of the mobile device, by leveraging a vulnerability of the system, hence sending back the collected information to some remote web service. In this paper, we consider a different adversary, who does not interact actively with the mobile device, but he is able to eavesdrop the network traffic of the device from the network side (e.g., controlling a Wi-Fi access point). The fact that the network traffic is often encrypted makes the attack even more challenging. In this paper, we investigate to what extent such an external attacker can identify the specific actions that a user is performing on her mobile apps. We design a system that achieves this goal using advanced machine learning techniques. We built a complete implementation of this system, and we also run a thorough set of experiments, which show that our attack can achieve accuracy and precision higher than 95%, for most of the considered actions. We compared our solution with the three state-of-the-art algorithms, and confirming that our system outperforms all these direct competitors.

Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma

ObjectiveTo evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma. Materials and MethodsWe integrated the Epic® electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments. Patterns of CDS review included either a delayed, near-real-time review, where the physician viewed CDS recommendations generated by the nursing assessment, or a real-time review, where the physician viewed recommendations generated by their own documentation. A backstopping, vendor-based CDS triggered with zero delay when no recommendation was available in the EHR from the web-service. We assessed the execution characteristics of the integrated system and the source of the generated recommendations viewed by physicians. ResultsThe ECRS mean execution time was 0.74 ±0.72s. Overall execution time was substantially different at the two sites, with mean total transaction times of 19.67 and 3.99s. Of 1930 analyzed transactions from the two sites, 60% (310/521) of all physician documentation-initiated recommendations and 99% (1390/1409) of all nurse documentation-initiated recommendations originated from the remote web service. DiscussionThe remote CDS system was the source of recommendations in more than half of the real-time cases and virtually all the near-real-time cases. Comparisons are limited by allowable variation in user workflow and resolution of the EHR clock. ConclusionWith maturation and adoption of standards for CDS services, remote CDS shows promise to decrease time-to-trial for multicenter evaluations of candidate decision support interventions.

"Not just another walking program": Everyday Activity Supports You (EASY) model-a randomized pilot study for a parallel randomized controlled trial.

BackgroundMaintaining physical activity is an important goal with positive health benefits, yet many people spend most of their day sitting. Our Everyday Activity Supports You (EASY) model aims to encourage movement through daily activities and utilitarian walking. The primary objective of this phase was to test study feasibility (recruitment and retention rates) for the EASY model.MethodsThis 6-month study took place in Vancouver, Canada, from May to December 2013, with data analyses in February 2014. Participants were healthy, inactive, community-dwelling women aged 55–70 years. We recruited through advertisements in local community newspapers and randomized participants using a remote web service. The model included the following: group-based education and social support, individualized physical activity prescription (called Activity 4-1-1), and use of a Fitbit activity monitor. The control group received health-related information only. The main outcome measures were descriptions of study feasibility (recruitment and retention rates). We also collected information on activity patterns (ActiGraph GT3X+ accelerometers) and health-related outcomes such as body composition (height and weight using standard techniques), blood pressure (automatic blood pressure monitor), and psychosocial variables (questionnaires).ResultsWe advertised in local community newspapers to recruit participants. Over 3 weeks, 82 participants telephoned; following screening, 68% (56/82) met the inclusion criteria and 45% (25/56) were randomized by remote web-based allocation. This included 13 participants in the intervention group and 12 participants in the control group (education). At 6 months, 12/13 (92%) intervention and 8/12 (67%) control participants completed the final assessment. Controlling for baseline values, the intervention group had an average of 2,080 [95% confidence intervals (CIs) 704, 4,918] more steps/day at 6 months compared with the control group. There was an average between group difference in weight loss of −4.3 [95% CI −6.22, −2.40] kg and reduction in diastolic blood pressure of −8.54 [95% CI −16.89, −0.198] mmHg, in favor of EASY.ConclusionsThe EASY pilot study was feasible to deliver; there was an increase in physical activity and reduction in weight and blood pressure for intervention participants at 6 months.Trial registrationClinicalTrials.gov identifier: NCT01842061 Electronic supplementary materialThe online version of this article (doi:10.1186/2055-5784-1-4) contains supplementary material, which is available to authorized users.

Geospatial data sharing, online spatial analysis and processing of Indian Biodiversity data in Internet GIS domain – A case study for raster based online geo-processing

Abstract. National Biodiversity Characterization at Landscape Level, a project jointly sponsored by Department of Biotechnology and Department of Space, was implemented to identify and map the potential biodiversity rich areas in India. This project has generated spatial information at three levels viz. Satellite based primary information (Vegetation Type map, spatial locations of road & village, Fire occurrence); geospatially derived or modelled information (Disturbance Index, Fragmentation, Biological Richness) and geospatially referenced field samples plots. The study provides information of high disturbance and high biological richness areas suggesting future management strategies and formulating action plans. The study has generated for the first time baseline database in India which will be a valuable input towards climate change study in the Indian Subcontinent. The spatial data generated during the study is organized as central data repository in Geo-RDBMS environment using PostgreSQL and POSTGIS. The raster and vector data is published as OGC WMS and WFS standard for development of web base geoinformation system using Service Oriented Architecture (SOA). The WMS and WFS based system allows geo-visualization, online query and map outputs generation based on user request and response. This is a typical mashup architecture based geo-information system which allows access to remote web services like ISRO Bhuvan, Openstreet map, Google map etc., with overlay on Biodiversity data for effective study on Bio-resources. The spatial queries and analysis with vector data is achieved through SQL queries on POSTGIS and WFS-T operations. But the most important challenge is to develop a system for online raster based geo-spatial analysis and processing based on user defined Area of Interest (AOI) for large raster data sets. The map data of this study contains approximately 20 GB of size for each data layer which are five in number. An attempt has been to develop system using python, PostGIS and PHP for raster data analysis over the web for Biodiversity conservation and prioritization. The developed system takes inputs from users as WKT, Openlayer based Polygon geometry and Shape file upload as AOI to perform raster based operation using Python and GDAL/OGR. The intermediate products are stored in temporary files and tables which generate XML outputs for web representation. The raster operations like clip-zip-ship, class wise area statistics, single to multi-layer operations, diagrammatic representation and other geo-statistical analysis are performed. This is indigenous geospatial data processing engine developed using Open system architecture for spatial analysis of Biodiversity data sets in Internet GIS environment. The performance of this applications in multi-user environment like Internet domain is another challenging task which is addressed by fine tuning the source code, server hardening, spatial indexing and running the process in load balance mode. The developed system is hosted in Internet domain (http://bis.iirs.gov.in) for user access.

An Online Performance Prediction Framework for Service-Oriented Systems

The exponential growth of Web service makes building high-quality service-oriented systems an urgent and crucial research problem. Performance of the service-oriented systems highly depends on the remote Web services as well as the unpredictability of the Internet. Performance prediction of service-oriented systems is critical for automatically selecting the optimal Web service composition. Since the performance of Web services is highly related to the service status and network environments which are variable over time, it is an important task to predict the performance of service-oriented systems at run-time. To address this critical challenge, this paper proposes an online performance prediction framework, called OPred, to provide personalized service-oriented system performance prediction efficiently. Based on the past usage experience from different users, OPred builds feature models and employs time series analysis techniques on feature trends to make performance prediction. The results of large-scale real-world experiments show the effectiveness and efficiency of OPred.

Web services-based text-mining demonstrates broad impacts for interoperability and process simplification.

The Critical Assessment of Information Extraction systems in Biology (BioCreAtIvE) challenge evaluation tasks collectively represent a community-wide effort to evaluate a variety of text-mining and information extraction systems applied to the biological domain. The BioCreative IV Workshop included five independent subject areas, including Track 3, which focused on named-entity recognition (NER) for the Comparative Toxicogenomics Database (CTD; http://ctdbase.org). Previously, CTD had organized document ranking and NER-related tasks for the BioCreative Workshop 2012; a key finding of that effort was that interoperability and integration complexity were major impediments to the direct application of the systems to CTD's text-mining pipeline. This underscored a prevailing problem with software integration efforts. Major interoperability-related issues included lack of process modularity, operating system incompatibility, tool configuration complexity and lack of standardization of high-level inter-process communications. One approach to potentially mitigate interoperability and general integration issues is the use of Web services to abstract implementation details; rather than integrating NER tools directly, HTTP-based calls from CTD's asynchronous, batch-oriented text-mining pipeline could be made to remote NER Web services for recognition of specific biological terms using BioC (an emerging family of XML formats) for inter-process communications. To test this concept, participating groups developed Representational State Transfer /BioC-compliant Web services tailored to CTD's NER requirements. Participants were provided with a comprehensive set of training materials. CTD evaluated results obtained from the remote Web service-based URLs against a test data set of 510 manually curated scientific articles. Twelve groups participated in the challenge. Recall, precision, balanced F-scores and response times were calculated. Top balanced F-scores for gene, chemical and disease NER were 61, 74 and 51%, respectively. Response times ranged from fractions-of-a-second to over a minute per article. We present a description of the challenge and summary of results, demonstrating how curation groups can effectively use interoperable NER technologies to simplify text-mining pipeline implementation.Database URL: http://ctdbase.org/

The Research on Intelligent Agricultural Information Monitoring System Based on Embedded Platform

Aiming at the fact that node information collection efficiency of agricultural monitoring system is not high, lack of remote monitoring capabilities and other issues, the paper design the system of intelligent agricultural information monitoring system based on embedded.Using epoll model to implement acquisition node information and control function improves I/O efficiency; Applying Boa framework provides remote monitoring Web services to enhance the system's remote monitoring capabilities; In order to meet the demands of long-distance transmission ,the paper uses ffmpeg library to make efficient video compression.The test result show that the system can efficiently process the nodes monitoring parameters and video data , better real-time in remote monitoring terminal, higher stability,havings a positive meaning in promoting agricultural information.

Personalized Reliability Prediction of Web Services

Service Oriented Architecture (SOA) is a business-centric IT architectural approach for building distributed systems. Reliability of service-oriented systems heavily depends on the remote Web services as well as the unpredictable Internet connections. Designing efficient and effective reliability prediction approaches of Web services has become an important research issue. In this article, we propose two personalized reliability prediction approaches of Web services, that is, neighborhood-based approach and model-based approach. The neighborhood-based approach employs past failure data of similar neighbors (either service users or Web services) to predict the Web service reliability. On the other hand, the model-based approach fits a factor model based on the available Web service failure data and use this factor model to make further reliability prediction. Extensive experiments are conducted with our real-world Web service datasets, which include about 23 millions invocation results on more than 3,000 real-world Web services. The experimental results show that our proposed reliability prediction approaches obtain better reliability prediction accuracy than other competing approaches.

Taking entity reconciliation offline

AbstractEntity reconciliation—linking names or terms to identifiers in external datasets—is a popular method of adding standardized structured data to loosely structured documents. Most approaches to entity reconciliation rely on remote web services, requiring network access during the reconciliation process. For use cases that rely on a “human in the loop” (reconciling entities during the authoring process), this requirement may be a problem. To address this problem, we investigated the feasibility of offline entity reconciliation against the Virtual International Authority File. Offline entity reconciliation was implemented by taking advantage of newly standardized browser storage interfaces to store and query parts of this large dataset locally. We present the results of this investigation and our comparison of the performance, scalability, ease of implementation, and cross‐browser compatibility of the various options for storing entity data locally.

A Perspective on Resource Synchronization

Web applications frequently leverage resources made available by remote web servers. As resources are created, updated, deleted, or moved, these applications face challenges to remain in lockstep with changes on the server. Several approaches exist to help meet this challenge for use cases where good enough synchronization is acceptable. But when strict resource coverage or low synchronization latency is required, commonly accepted Web-based solutions remain illusive. This paper provides a perspective on the resource synchronization problem that results from inspiration gained from prior work, and initial insights resulting from the recently launched NISO/OAI ResourceSync effort.

Dominance-Based Service Selection Scheme with Concurrent Requests

In dynamic Web service environments, the performance of the Internet is unpredictable; the reliability and effectiveness of remote Web services are also unclear. Therefore, it can hardly be guaranteed that the quality of Web service (QoWS) attributes of Web services do not fluctuate with the dynamic Web service environments. When a composite service is planned in the context of dynamic service environments, there is another aspect which has not been taken into account by existing works, namely, concurrency - the fact that multiple requests to a composite service may arrive at the same time. Considering the dynamics of Web service environments and concurrency of requests, we propose in this paper a service selection scheme which adopts top-k dominating queries to generate a composition solution rather than only select the best composition solution for a given request. The experimental results have investigated the efficiency and effectiveness of our approach and shown that it outperforms baseline and traditional methods for service selection.

Workflows for microarray data processing in the Kepler environment

BackgroundMicroarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services.ResultsWe developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R/BioConductor scripting approaches to pipeline design. Finally, we suggest that microarray data processing task workflows may provide a basis for future example-based comparison of different workflow systems.ConclusionsWe provide a set of tools and complete workflows for microarray data analysis in the Kepler environment, which has the advantages of offering graphical, clear display of conceptual steps and parameters and the ability to easily integrate other resources such as remote data and web services.

Caching Mechanism in Peer-to-Peer Networks through Active XML

Active XML (AXML) is a new markup language framework that provides the ability to exchange intensional data. The intensional data is defined in the AXML documents as calls to local or remote Web services. AXML aims to improve the task partition and distribution in P2P networks. However, if one peer joins more than one P2P network and its services are invoked frequently by a large number of peers, this peer can become a bottleneck and requires large computational resource. In this paper we show that a caching mechanism in P2P networks based on the AXML technology can be a promising solution because AXML properties will simplify the caching procedures in these networks. We propose three layers of caches that will be located in: the bottleneck service provider, nominated peer(s) in the P2P network and the service requester. Index Terms—Active XML, Web Service, Peer-to-Peer

EN

The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

Sprint

Remote data access latency is a significant performance bottleneck in many modern programs that use remote databases and web services. We present Sprint - a run-time system for optimizing such programs by prefetching and caching data from remote sources in parallel to the execution of the original program. Sprint separates the concerns of exposing potentially-independent data accesses from the mechanism for executing them efficiently in parallel or in a batch. In contrast to prior work, Sprint can efficiently prefetch data in the presence of irregular or input-dependent access patterns, while preserving the semantics of the original program. We used Sprint to automatically improve the performance of several real-world Java programs that access remote databases (MySQL, DB2) and web services (Facebook, IBM's Yellow Pages). Sprint achieves speedups ranging 2.4x to 15.8x over sequential execution, which are comparable to those achieved by manually modifying the program for asynchronous and batch execution of data accesses. Sprint provides a simple interface that allows a programmer to plug in support for additional data sources without modifying the client program.