2438435
Real-time new event detection for video streams
Online detection of video clips that present previously unseen events in a video stream is still an open challenge to date. For this online new event detection (ONED) task, existing studies mainly focus on optimizing the detection accuracy instead of the detection efficiency. As a result, it is difficult for existing systems to detect new events in real time, especially for large-scale video collections such as the video content available on the Web. In this paper, we propose several scalable techniques to improve the video processing speed of a baseline ONED system by orders of magnitude without sacrificing much detection accuracy. First, we use text features alone to filter out most of the non-new-event clips and to skip those expensive but unnecessary steps including image feature extraction and image similarity computation. Second, we use a combination of indexing and compression methods to speed up text processing. We implemented a prototype of our optimized ONED system on top of IBM's System S. The effectiveness of our techniques is evaluated on the standard TRECVID 2005 benchmark, which demonstrates that our techniques can achieve a 480-fold speedup with detection accuracy degraded less than 5%.
7442505
Transaction Reordering and Grouping for Continuous Data Loading
With the increasing popularity of operational data warehousing, the ability to load data quickly and continuously into an RDBMS is becoming more and more important. However, in the presence of materialized join views, loading data concurrently into multiple base relations of the same materialized join view can cause a severe deadlock problem. To solve this problem, we propose reordering the data to be loaded so that at any time, for any materialized join view, data is only loaded into one of its base relations. Also, for load transactions on the relations that contain "aggregate" attributes, we propose using pre-aggregation to reduce the number of SQL statements in the load transactions. The advantages of our methods are demonstrated through experiments with a commercial parallel RDBMS.
53228070
Transaction reordering with application to synchronized scans
Traditional workload management methods mainly focus on the current system status while information about the interaction between queued and running transactions is largely ignored. An exception to this is the transaction reordering method, which reorders the transaction sequence submitted to the RDBMS and improves the transaction throughput by considering both the current system status and information about the interaction between queued and running transactions. The existing transaction reordering method only considers the reordering opportunities provided by analyzing the lock conflict information among multiple transactions. This significantly limits the applicability of the transaction reordering method. In this paper, we extend the existing transaction reordering method into a general transaction reordering framework that can incorporate various factors as the reordering criteria. We show that by analyzing the resource utilization information of transactions, the transaction reordering method can also improve the system throughput by increasing the resource sharing opportunities among multiple transactions. We provide a concrete example on synchronized scans and demonstrate the advantages of our method through experiments with a commercial parallel RDBMS.
14863037
Resource-adaptive real-time new event detection
In a document streaming environment, online detection of the first documents that mention previously unseen events is an open challenge. For this online new event detection (ONED) task, existing studies usually assume that enough resources are always available and focus entirely on detection accuracy without considering efficiency. Moreover, none of the existing work addresses the issue of providing an effective and friendly user interface. As a result, there is a significant gap between the existing systems and a system that can be used in practice. In this paper, we propose an ONED framework with the following prominent features. First, a combination of indexing and compression methods is used to improve the document processing rate by orders of magnitude without sacrificing much detection accuracy. Second, when resources are tight, a resource-adaptive computation method is used to maximize the benefit that can be gained from the limited resources. Third, when the new event arrival rate is beyond the processing capability of the consumer of the ONED system, new events are further filtered and prioritized before they are presented to the consumer. Fourth, implicit citation relationships are created among all the documents and used to compute the importance of document sources. This importance information can guide the selection of document sources. We implemented a prototype of our framework on top of IBM's Stream Processing Core middleware. We also evaluated the effectiveness of our techniques on the standard TDT5 benchmark. To the best of our knowledge, this is the first implementation of a real application in a large-scale stream processing system.
11082409
Answering relationship queries on the web
Finding relationships between entities on the Web, e.g., the connections between different places or the commonalities of people, is a novel and challenging problem. Existing Web search engines excel in keyword matching and document ranking, but they cannot well handle many relationship queries. This paper proposes a new method for answering relationship queries on two entities. Our method first respectively retrieves the top Web pages for either entity from a Web search engine. It then matches these Web pages and generates an ordered list of Web page pairs. Each Web page pair consists of one Web page for either entity. The top ranked Web page pairs are likely to contain the relationships between the two entities. One main challenge in the ranking process is to effectively filter out the large amount of noise in the Web pages without losing much useful information. To achieve this, our method assigns appropriate weights to terms in Web pages and intelligently identifies the potential connecting terms that capture the relationships between the two entities. Only those top potential connecting terms with large weights are used to rank Web page pairs. Finally, the top ranked Web page pairs are presented to the searcher. For each such pair, the query terms and the top potential connecting terms are properly highlighted so that the relationships between the two entities can be easily identified. We implemented a prototype on top of the Google search engine and evaluated it under a wide variety of query scenarios. The experimental results show that our method is effective at finding important relationships with low overhead.
11663917
On iterative intelligent medical search
Searching for medical information on the Web has become highly popular, but it remains a challenging task because searchers are often uncertain about their exact medical situations and unfamiliar with medical terminology. To address this challenge, we have built an intelligent medical Web search engine called iMed, which uses medical knowledge and an interactive questionnaire to help searchers form queries. This paper focuses on iMed's iterative search advisor, which integrates medical and linguistic knowledge to help searchers improve search results iteratively. Such an iterative process is common for general Web search, and especially crucial for medical Web search, because searchers often miss desired search results due to their limited medical knowledge and the task's inherent difficulty. iMed's iterative search advisor helps the searcher in several ways. First, relevant symptoms and signs are automatically suggested based on the searcher's description of his situation. Second, instead of taking for granted the searcher's answers to the questions, iMed ranks and recommends alternative answers according to their likelihoods of being the correct answers. Third, related MeSH medical phrases are suggested to help the searcher refine his situation description. We demonstrate the effectiveness of iMed's iterative search advisor by evaluating it using real medical case records and USMLE medical exam questions.
22377735
Failure-Equivalent Transformation of Transition Systems to Avoid Internal Actions
Abstract Labelled transition systems are often used as a theoretical framework for modelling communication protocols or distributed software systems. In order to model the deadlock properties of the systems, the internal transitions of the submodules are often represented globally by so-called internal actions. However, certain verification and testing methods assume that the specification of the system is given in the form of a transition system without internal actions. This paper shows that most labelled transition systems with internal actions can be transformed into a failure-equivalent labelled transition system without internal actions. A sufficient condition is given, and an algorithm is described which does the transformation for any transition system which satisfies the condition. This algorithm can be applied to use the above verification and testing methods also for specification including internal actions.
13494891
Tracking Telescope Aiming Point for Bioptic Driving Surveillance
Bioptic telescope is a visual aid used by some people with impaired vision for driving and to qualify for licensing. Data on how and when bioptic drivers use the telescope and what they look at with it are important in biop- tic driving studies. A video-based technique to track bioptic drivers' spectacle frames, which represent telescope aiming point, is presented in this paper. With three retro-reflective markers pasted on the bioptic spectacles frame, aiming point is determined from the angles formed by the three markers. Telescope aiming points projected on a scene camera image is calculated by means of interpolation based on a novel calibration method in which a laser pointer is mounted on the spectacle frame. A large number of calibration points are sampled automatically when the driver scans across the scene. Preliminary experiment demonstrated that the average error over a 65° ×48° field was only 0.89 degree.
2819430
Comments on "Leading-One Prediction with Concurrent Position Correction"
In this report, we first point out and analyse an error in the implementation of the pre-encoding logic in the LOP module proposed in [1], and then present a modification method.
10608907
Development and Evaluation of Vision Multiplexing Devices for Vision Impairments
We have proposed a novel concept of vision multiplexing for the visually impaired - superimposing contour images over their natural view of a scene or over original images presented on a TV screen. We have implemented the concept using an optical see-through head mounted display to provide either visual field expansion to patients with peripheral field loss or vision enhancement to patients with central vision loss. We have also implemented the concept in a video player with dynamic magnification for patients with central vision loss. Results of initial testing in the lab and on the street are promising.
15413027
Research on Steganalysis for Text Steganography Based on Font Format
In the research area of text steganography, algorithms based on font format have advantages of great capacity, good imperceptibility and wide application range. However, little work on steganalysis for such algorithms has been reported in the literature. Based on the fact that the statistic features of font format will be changed after using font-format-based steganographic algorithms, we present a novel Support Vector Machine-based steganalysis algorithm to detect whether hidden information exists or not. This algorithm can not only effectively detect the existence of hidden information, but also estimate the hidden information length according to variations of font attribute value. As shown by experimental results, the detection accuracy of our algorithm reaches as high as 99.3% when the hidden information length is at least 16 bits.