35665703
Implementation of QoS-Provisioning system for voice over IP
In this paper, we address issues related to implementing Voice-over-IP (VoIP) services in packet switching networks. VoIP has been identified as a critical real-time application in the network QoS research community and has been implemented in commercial products. To provide competent quality of service for VoIP, the call admission control (CAC) mechanism has to be introduced to prevent packet losing and over-queuing. Several well-designed CAC mechanisms, such as the Site- Utilization-Based CAC and the link-utilization-based CAC mechanisms, are in place. However, the existing commercial VoIP systems have not been able to adequately apply and support these CAC mechanisms, and hence unable to provide QoS guarantees to VoIP. We have designed and implemented a QoS-Provisioning system that can be seamlessly integrated to the existing VoIP system to overcome its weakness in offering QoS guarantees. As a result, our system has been realized at Internet2 Voice Over IP Testbed in Texas A&M University.
8639082
Delay Analysis in Temperature-Constrained Hard Real-Time Systems with General Task Arrivals
In this paper, we study temperature-constrained hard real-time systems, where real-time guarantees must be met without exceeding safe temperature levels within the processor. Dynamic speed scaling is one of the major techniques to manage power so as to maintain safe temperature levels. As example, we adopt a simple reactive speed control technique in our work. We design a methodology to perform delay analysis for general task arrivals under reactive speed control with first-in-first-out (FIFO) scheduling and static-priority (SP) scheduling. As a special case, we obtain a close-form delay formula for the leaky-bucket task arrival model. Our data show how simple reactive speed control can decrease the delay of tasks compared with any constant-speed scheme
42912843
NChiql: The Chinese Natural Language Interface to Databases
Numerous natural language interface to databases (NLIDBs) developed in the mid-eighties demonstrated impressive characteristic in certain application areas, but NLIDBs did not gained the expected rapid and wide commercial acceptance. We argue that there are two good reasons explain why: limited portability and poor usability. This paper describes the design and implementation of NChiql, a Chinese natural language interface to databases. In order to bright the essence of these problems, we provide an abstract model (AM) in NChiql. We try to give a solution for these problems based on the model in our system. In this paper, we depict a novel method based on database semantics (SCM) to handle the Chinese natural language query, which greatly promotes the system's usability. The experiments show that NChiql has good usability and high correctness.
13593931
Design and implementation of a comprehensive outpatient Results Manager
Prior research has demonstrated that clinicians often fail to review and act upon outpatient test results in a timely and appropriate manner. To address this patient safety and quality of care issue, Partners Healthcare has developed a browser-based, provider-centric, comprehensive results management application to help clinic physicians review and act upon test results in a safe, reliable, and efficient manner. The application, called the Results Manager, incorporates extensive decision support features to classify the degree of abnormality for each result, presents guidelines to help clinicians manage abnormal results, allows clinicians to generate result letters to patients with predefined, context-sensitive templates and prompts physicians to set reminders for future testing. In this paper, we outline the design process and functionality of Results Manager. We also discuss its underlying architectural design, which revolves around a clinical event monitor and a rules engine, and the methodological challenges encountered in designing this application.
554747
Image-Segmentation Evaluation From the Perspective of Salient Object Extraction
Image segmentation and its performance evaluation are very difficult but important problems in computer vision. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity: For general-purpose segmentation, the ground truth and segmentation accuracy may not be well defined, while embedding the evaluation in a specific application, the evaluation results may not be extended to other applications. We present in this paper a new benchmark for evaluating image segmentation. Specifically, we formulate image segmentation as identifying the single most perceptually salient structure from an image. We collect a large variety of test images that conforms to this specific formulation, construct unambiguous ground truth for each image, and define a reliable way to measure the segmentation accuracy. We then present two special strategies to further address two important issues: (a) the most salient structures in some real images may not be unique or unambiguously defined, and (b) many available image-segmentation methods are not developed to directly extract a single salient structure. Finally, we apply this benchmark to evaluate and compare the performance of several state-of-the-art image-segmentation methods, including the normalized-cut method, the level-set method, the efficient graph-based method, the mean-shift method, and the ratio-contour method.
11079160
An Anonymous Endorsement System
The expression of one’s opinion through endorsement is one of the simplest methods of democratic participation. The result of an endorsement can be used to evaluate whether a certain subject should deserve a higher attention. In some cases, the endorsers desire privacy protection. However, conventional paper-based endorsement systems provide neither convenience nor well privacy protection for the endorsers. In addition, current electronic anonymous voting schemes are unsuitable for anonymous endorsement. This motivates us to develop an anonymous endorsement system that can be realized on computer networks. The proposed system satisfies completeness, soundness, privacy, unreusability, eligibility, and verifiability. In practice, the proposed system can be integrated with the conventional paper-based endorsement system.
35567316
Computational Analysis of Gene Identification with SAGE
SAGE is one of the few techniques capable of uniformly probing gene expression at a genome level irrespective of mRNA abundance and without a priori knowledge of the transcripts present. However, individual SAGE tags can match many sequences in the reference database, complicating gene identification. We perform a baseline evaluation of gene identification with SAGE using UniGene Human as the reference database by analyzing 1) the distributions of tags for various length tag sets formed for UniGene Human and 2) the tag-to-sequence mapping using a SAGE tag set consisting of 37,522 tags derived from human myeloid cells. The extensive multiplicity of the dbEST component of UniGene significantly detracts from gains that might be expected by extending tags within the scope of the SAGE protocol. In order to achieve reasonable sequence specificity for gene identification with the content of the commonly used UniGene sequence collection, tags on the order of hundreds of bases in length are required. One way to produce tags of such lengths is with GLGI, which extends SAGE tags to the 3' end of cDNA. We show that the longer sequences produced by GLGI relieve significantly the multiple match condition. In the myeloid sample, we also found a correlation between multiple match severity and high copy number. We extrapolate these findings, providing insights into the use of UniGene Human as a reference for gene identification.