14324910
Challenging issues in iterative intelligent medical search
Searching for medical information on the Web is highly popular these days. To facilitate ordinary people to perform medical search and preliminary disease self-diagnosis, we have built an intelligent medical Web search engine called iMed. iMed introduces and extends pattern recognition and expert system technology into the search engine domain. It uses medical knowledge and an interactive questionnaire to help searchers form queries. Due to searcherspsila limited medical knowledge and the taskpsilas inherent difficulty, searchers often cannot find desired search results in a single pass and have to search iteratively for multiple passes. For this purpose, iMed provides an iterative search advisor that guides searchers to refine their inputs. Based on our experience in building and using iMed, this paper summarizes the common difficulties faced by ordinary medical information searchers and the research issues that deserve attention from people working in the pattern recognition and medical search areas.
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.
235091
Efficient detection of empty-result queries
Frequently encountered in query processing, empty query results usually do not provide users with much useful information. Yet, users might still have to wait for a long time before they disappointingly realize that their results are empty. To significantly reduce such unfavorable delays, in this paper, we propose a novel method to quickly detect, without actual execution, those queries that will return empty results. Our key idea is to remember and reuse the results from previously-executed, empty-result queries. These results are stored in the form of so-called atomic query parts so that the (partial) results from multiple queries can be combined together to handle a new query without incurring much overhead. To increase our chance of detecting empty-result queries with only a limited storage, our method (1) stores the most "valuable" information about empty-result queries, (2) removes redundant information among different empty-result queries, (3) continuously updates the stored information to adapt to the current query pattern, and (4) utilizes a set of special properties of empty results. We evaluate the efficiency of our method through a theoretical analysis and an initial implementation in PostgreSQL. The results show that our method has low overhead and can often successfully avoid executing empty-result queries.
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.
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.
17174750
Test Selection Based on Communicating Nondeterministic Finite-State Machines Using a Generalized WP-Method
Presents a method of generating test sequences for concurrent programs and communication protocols that are modeled as communicating nondeterministic finite-state machines (CNFSMs). A conformance relation, called trace-equivalence, is defined within this model, serving as a guide to test generation. A test generation method for a single nondeterministic finite-state machine (NFSM) is developed, which is an improved and generalized version of the Wp-method that generates test sequences only for deterministic finite-state machines. It is applicable to both nondeterministic and deterministic finite-state machines. When applied to deterministic finite-state machines, it yields usually smaller test suites with full fault coverage than the existing methods that also provide full fault coverage, provided that the number of states in implementation NFSMs are bounded by a known integer. For a system of CNFSMs, the test sequences are generated in the following manner: a system of CNFSMs is first reduced into a single NFSM by reachability analysis; then the test sequences are generated from the resulting NFSM using the generalized Wp-method. >
44490004
Fault Models in Testing
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.
30097914
Improved Method for Network Danger Evaluation Based on Immunology Principle
This paper proposes an improved immunological surveillance for network danger evaluation model, focusing on intrusion detection and countermeasures with respect to widely-used networks. An improved intrusion detection mechanism based on self-tolerance, clone selection, and immune surveillance is established. A new network security evaluation method using antibody concentration to quantitatively analyze the degree of intrusion danger level is presented. Additionally, this new hierarchical management framework of the proposed model adopt to improve the detection efficiency and to overcome the shortcoming of the local optimum. The experimental results show that the proposed model is a good solution for network security evaluation.
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.