227525
Integrated RFID data modeling: an approach for querying physical objects in pervasive computing
Radio frequency identiﬂcation(RFID) technology uses radio-frequency waves to transfer data between readers and mov-able tagged objects without line of sight. RFID holds thepromise of real-time identifying, locating, tracking and mon-itoring physical objects, and can be used for a wide range ofpervasive computing applications. To achieve these goals,RFID data have to be collected, transformed and expres-sively modeled as their virtual counterparts in the virtualworld. RFID data, however, have their own unique char-acteristics { including aggregation, location, temporal andhistory-oriented { which have to be fully considered and inte-grated into the data model. The diversity of RFID applica-tions pose further challenges to a generalized framework forRFID data modeling. In this paper, we explore the funda-mental characteristics of RFID data and classify RFID ap-plications into a set of typical scenarios. We then propose ageneralized RFID data modeling framework with constructsfor each typical scenario. These constructs can be combinedto model most RFID applications in real world.
6631927
Ctree: a compact tree for indexing XML data
In this paper, we propose a novel compact tree (Ctree) for XML indexing, which provides not only concise path summaries at the group level but also detailed child-parent links at the element level. Group level mapping allows efficient pruning of a large search space while element level mapping provides fast access to the parent of an element. Due to the tree nature of XML data and queries, such fast child-to-parent access is essential for efficient XML query processing. Using group-based element reference, Ctree enables the clustering of inverted lists according to groups, which provides efficient join between inverted lists and structural index group extents. Our experiments reveal that Ctree is efficient for processing both single-path and branching queries with various value predicates.
11533048
RFID Data Processing with a Data Stream Query Language
RFID technology provides significant advantages over traditional object-tracking technologies and is increasingly adopted and deployed in real applications. RFID applications generate large volume of streaming data, which have to be automatically filtered, processed, and transformed into semantic data, and integrated into business applications. Indeed, RFID data are highly temporal, and RFID observations form complex temporal event patterns which can be very different for various RFID applications. Thus, it is desirable to have a general RFID data processing framework with a powerful language, for the end users to express a variety of queries on RFID data streams, as well as detecting complex events patterns. While data stream management systems (DSMSs) are emerging for optimized stream data processing, they usually lack the language construct support for temporal event detection. In this paper, we discuss a stream query language to provide comprehensive temporal event detection, through temporal operators and extension of sliding-window constructs. With the integration of temporal event detection, a DSMS has the capability to serve as a powerful system for RFID data processing.
1275297
Bridging Physical and Virtual Worlds: Complex Event Processing for RFID Data Streams
Advances of sensor and RFID technology provide significant new power for humans to sense, understand and manage the world. RFID provides fast data collection with precise identification of objects with unique IDs without line of sight, thus it can be used for identifying, locating, tracking and monitoring physical objects. Despite these benefits, RFID poses many challenges for data processing and management: i) RFID observations contain duplicates, which have to be filtered; ii) RFID observations have implicit meanings, which have to be transformed and aggregated into semantic data represented in their data models; and iii) RFID data are temporal, streaming, and in high volume, and have to be processed on the fly. Thus, a general RFID data processing framework is needed to automate the transformation of physical RFID observations into the virtual counterparts in the virtual world linked to business applications. In this paper, we take an event-oriented approach to process RFID data, by devising RFID application logic into complex events. We then formalize the specification and semantics of RFID events and rules. We demonstrate that traditional ECA event engine cannot be used to support highly temporally constrained RFID events, and develop an RFID event detection engine that can effectively process complex RFID events. The declarative event-based approach greatly simplifies the work of RFID data processing, and significantly reduces the cost of RFID data integration.
14446563
Vague Content and Structure (VCAS) Retrieval for Document-centric XML Collections
document-centric XML collections with structure conditions improves retrieval precisions. The structures of such XML collections, however, are often too complex for users to fully grasp. Thus, for queries regarding such collections, it is more appropriate to retrieve answers that approximately match the structure and content conditions in these queries, a process also known as vague content and structure (VCAS) retrieval. Most existing XML engines, however, only support content-only (CO) retrieval and/or strict content and structure (SCAS) retrieval. To remedy these shortcomings, we propose an approach for VCAS retrieval using existing XML engines. Our approach first decomposes a VCAS query into a SCAS sub-query and a CO sub- query, then uses existing XML engines to retrieve SCAS results and CO results for the decomposed sub-queries, and finally combines results from both retrievals to produce approximate results for the original query. Further, to improve retrieval precision, we propose two similarity metrics to adjust the scores of CO retrieval results by their relevancies to the path condition for the original query target. We evaluate our VCAS retrieval approach through extensive experiments with the INEX 04 XML collection and VCAS query sets. The experimental results demonstrate the effectiveness of our VCAS retrieval approach.
5842197
Configurable indexing and ranking for XML information retrieval
Indexing and ranking are two key factors for efficient and effective XML information retrieval. Inappropriate indexing may result in false negatives and false positives, and improper ranking may lead to low precisions. In this paper, we propose a configurable XML information retrieval system, in which users can configure appropriate index types for XML tags and text contents. Based on users' index configurations, the system transforms XML structures into a compact tree representation, Ctree, and indexes XML text contents. To support XML ranking, we propose the concepts of "weighted term frequency" and "inverted element frequency," where the weight of a term depends on its frequency and location within an XML element as well as its popularity among similar elements in an XML dataset. We evaluate the effectiveness of our system through extensive experiments on the INEX 03 dataset and 30 content and structure (CAS) topics. The experimental results reveal that our system has significantly high precision at low recall regions and achieves the highest average precision (0.3309) as compared with 38 official INEX 03 submissions using the strict evaluation metric.
36526611
Formal Engineering for Industrial Software Development - An Introduction to the SOFL Specification Language and Method
Formal methods have been developed as a rigorous approach to computer systems development over last three decades, but have been facing challenges in fighting for industrial acceptance in general. Most commonly used formal methods do not offer comprehensible structuring mechanism for building complex systems; formal refinement is not sufficient to deal with real development situations; and formal verification requires high skills and is time-intensive, and is therefore expensive to be adopted by industry.
1673600
Inferring Data Transformation Rules to Integrate Semantic Web Services
OWL-S allows selecting, composing and invoking Web Services at different levels of abstraction: selection uses high level abstract descriptions, invocation uses low level grounding ones, while composition needs to consider both high and low level descriptions. In our setting, two Web Services are to be composed so that output from the upstream one is used to create input for the downstream one. These Web Services may have different data models but are related to each other through high and low level descriptions. 
 
Correspondences must be found between components of the upstream data type and the downstream ones. Low level data transformation functions may be required (e.g. unit conversions, data type conversions). The components may be arranged in different XML tree structures. Thus, multiple data transformations are necessary: reshaping the message tree, matching leaves by corresponding types, translating through ontologies, and calling conversion functions. Our prototype compiles these transformations into a set of data transformation rules, using our tableau-based ALC Description Logic reasoner to reason over the given OWL-S and WSDL descriptions, as well as the related ontologies. A resolution-based inference mechanism for running these rules is embedded in an inference queue that conducts data from the upstream to the downstream service, running the rules to perform the data transformation in the process.
2425320
Scalable data aggregation for dynamic events in sensor networks
Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting-time which is used by nodes to wait for packets from their children before forwarding the packet to the sink. Although structureless approaches can address these issues, the performance does not scale well with the network size. We propose a semi-structured approach that uses a structureless technique locally followed by Dynamic Forwarding on an implicitly constructed packet forwarding structure to support network scalability. The structure, ToD, is composed of multiple shortest path trees. After performing local aggregation, nodes dynamically decide the forwarding tree based on the location of the sources. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2000 nodes network and real experiments on a 105 nodes Mica2-based network, we conclude that efficient aggregation in large scale networks can be achieved by our semi-structured approach.
11127695
The semantics of extended SOFL
SOFL (structured-object-based-formal language) has been extended to a formal object-oriented language and method while keeping its structured features. This extension allows powerful object-oriented reuse mechanisms, such as class inheritance and object composition, to be utilized in the early design phases. This paper presents the semantics for this extended SOFL, and further demonstrates the extendibility and reusability of the object-oriented semantic models of SOFL.
18046696
Motion Detection Circuits for a Time-To-Travel Algorithm
The paper describes a new motion detection circuit that extracts motion information based on a time-to-travel algorithm. The front-end photoreceptor adapts over 7 decades of background intensity and motion information can be extracted down to a contrast value of 2.5%. Results from the circuits which were fabricated in a 2-metal 2-poly 1.5mum CMOS process, show that the motion information can be extracted over 2 decades of speed.