A Comparative Study: Change Detection and Querying Dynamic XML Documents

The efficient management of the dynamic XML documents is a complex area of research. The changes and size of the XML documents throughout its lifetime are limitless. Change detection is an important part of version management to identify difference between successive versions of a document. Document content is continuously evolving. Users wanted to be able to query previous versions, query changes in documents, as well as to retrieve a particular document version efficiently. In this paper we provide comprehensive comparative analysis of various control schemes for change detection and querying dynamic XML documents

A Configuration Management System for Software Product Lines

Software product line engineering (SPLE) is a methodology for developing a family of software products in a particular domain by systematic reuse of shared code in order to improve product quality and reduce development time and cost. Currently, there are no software configuration management (SCM) tools that support software product line evolution. Conventional SCM tools are designed to support single product development. The use of conventional SCM tools forces developers to treat a software product line as a single software project by introducing new programming language constructs or using conditional compilation. We propose a research conguration management prototype called Molhado SPL that is designed specifically to support the evolution of software product lines. Molhado SPL addresses the evolution problem at the configuration level instead of at the code level. We studied the type of operations needed to support the evolution of software product lines and proposed a versioning model and eight cases of change propagation. Molhado SPL supports independent evolution of core assets and products, the sharing of code and the tracking relationships between products and shared code, and the eight cases of change propagation. The Molhado SPL consists of four layers with each layer providing a different type of service. At the heart of Molhado SPL are the versioning model, component object, shared component object, and project objects that allow for independent evolution of products and shared artifacts, for sharing, and for supporting change propagation. Furthermore,they allow product specific changes to shared code without interfering with the core asset that is shared. Products can also introduce product specific assets that only exist in that product. In order to for Molhado SPL to support product line, we implemented XML merging, feature model editing and debugging, and version-aware XML documents. To support merging of XML documents, we implemented a 3-way XML document merging algorithm that uses versioned data structures, change detection, and node identity. To support software product line derivation or modeling of software product line, we implemented support for feature model including editing and debugging. Finally, we created the version-aware XML document framework to support collaborative editing of XML documents without requiring a version repository. The version history is embedded in the documents using XML namespaces, so that the documents remain valid under the XML specification. The version-aware XML framework can also be used to support the exporting of documents from Molhado SPL repository to be edit outside and import back the change history made to the document. We evaluated Molhado SPL with two product lines: a document product line and a the graph data structures product line. This evaluation showed that Molhado SPL supports independently evolution of products and core assets and the eight change propagation cases. We did not evaluate MolhadoSPL in terms of scalability or usability. The main contributions of this dissertation research are: 1) Molhado SPL that supports the evolution of product lines, 2) a fast 3-way XML merge algorithm, 3) a version-aware XML document framework, and 4) a feature model editor and debugger

Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings

Semantic web technologies for video surveillance metadata

Video surveillance systems are growing in size and complexity. Such systems typically consist of integrated modules of different vendors to cope with the increasing demands on network and storage capacity, intelligent video analytics, picture quality, and enhanced visual interfaces. Within a surveillance system, relevant information (like technical details on the video sequences, or analysis results of the monitored environment) is described using metadata standards. However, different modules typically use different standards, resulting in metadata interoperability problems. In this paper, we introduce the application of Semantic Web Technologies to overcome such problems. We present a semantic, layered metadata model and integrate it within a video surveillance system. Besides dealing with the metadata interoperability problem, the advantages of using Semantic Web Technologies and the inherent rule support are shown. A practical use case scenario is presented to illustrate the benefits of our novel approach

Linking Text and Image with SVG

Annotation and linking (or referring) have been described as "scholarly primitives", basic methods used in scholarly research and publication of all kinds. The online publication of manuscript images is one basic use case where the need for linking and annotation is very clear. High resolution images are of great use to scholars and transcriptions of texts provide for search and browsing, so the ideal method for the digital publication of manuscript works is the presentation of page images plus a transcription of the text therein. This has become a standard method, but leaves open the questions of how deeply the linkages can be done and how best to handle the annotation of sections of the image. This paper presents a new method (named img2xml) for connecting text and image using an XML-based tracing of the text on the page image. The tracing method was developed as part of a series of experiments in text and image linking beginning in the summer of 2008 and will continue under a grant funded by the National Endowment for the Humanities. It employs Scalable Vector Graphics (SVG) to represent the text in an image of a manuscript page in a referenceable form and enables linking and annotation of the page image in a variety of ways. The paper goes on to discuss the scholarly requirements for tools that will be developed around the tracing method, and explores some of the issues raised by the img2xml method

BlogForever D2.4: Weblog spider prototype and associated methodology

The purpose of this document is to present the evaluation of different solutions for capturing blogs, established methodology and to describe the developed blog spider prototype

XML Schema-based Minification for Communication of Security Information and Event Management (SIEM) Systems in Cloud Environments

XML-based communication governs most of today's systems communication, due to its capability of representing complex structural and hierarchical data. However, XML document structure is considered a huge and bulky data that can be reduced to minimize bandwidth usage, transmission time, and maximize performance. This contributes to a more efficient and utilized resource usage. In cloud environments, this affects the amount of money the consumer pays. Several techniques are used to achieve this goal. This paper discusses these techniques and proposes a new XML Schema-based Minification technique. The proposed technique works on XML Structure reduction using minification. The proposed technique provides a separation between the meaningful names and the underlying minified names, which enhances software/code readability. This technique is applied to Intrusion Detection Message Exchange Format (IDMEF) messages, as part of Security Information and Event Management (SIEM) system communication hosted on Microsoft Azure Cloud. Test results show message size reduction ranging from 8.15% to 50.34% in the raw message, without using time-consuming compression techniques. Adding GZip compression to the proposed technique produces 66.1% shorter message size compared to original XML messages.Comment: XML, JSON, Minification, XML Schema, Cloud, Log, Communication, Compression, XMill, GZip, Code Generation, Code Readability, 9 pages, 12 figures, 5 tables, Journal Articl

Data Cleaning for XML Electronic Dictionaries via Statistical Anomaly Detection

Many important forms of data are stored digitally in XML format. Errors can occur in the textual content of the data in the fields of the XML. Fixing these errors manually is time-consuming and expensive, especially for large amounts of data. There is increasing interest in the research, development, and use of automated techniques for assisting with data cleaning. Electronic dictionaries are an important form of data frequently stored in XML format that frequently have errors introduced through a mixture of manual typographical entry errors and optical character recognition errors. In this paper we describe methods for flagging statistical anomalies as likely errors in electronic dictionaries stored in XML format. We describe six systems based on different sources of information. The systems detect errors using various signals in the data including uncommon characters, text length, character-based language models, word-based language models, tied-field length ratios, and tied-field transliteration models. Four of the systems detect errors based on expectations automatically inferred from content within elements of a single field type. We call these single-field systems. Two of the systems detect errors based on correspondence expectations automatically inferred from content within elements of multiple related field types. We call these tied-field systems. For each system, we provide an intuitive analysis of the type of error that it is successful at detecting. Finally, we describe two larger-scale evaluations using crowdsourcing with Amazon's Mechanical Turk platform and using the annotations of a domain expert. The evaluations consistently show that the systems are useful for improving the efficiency with which errors in XML electronic dictionaries can be detected.Comment: 8 pages, 4 figures, 5 tables; published in Proceedings of the 2016 IEEE Tenth International Conference on Semantic Computing (ICSC), Laguna Hills, CA, USA, pages 79-86, February 201