ppxscal/embedding_network huggingface dataset:
A rate control algorithm for VBR video encoding and transmission
Authors: Junfeng Bai
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

To satisfy the rigorous limitation of delay in real time transmission of high quality video, the coding rate and transmission rate should be selected judiciously. For the ATM variable bit rate (VBR) channel, the channel rate is tightly restrained by the traffic contract negotiated before communication. The leaky-bucket based rate control algorithm proposed by us could meet the delay and traffic contract, so as to abstain the cell loss over the user-network interface (UNI). Furthermore, in order to benefit the statistical multiplexing and improve the overall decoded video quality, the burstiness of the MPEG encoded stream is reduced dramatically in our system. Our experiment shows that the algorithm is a good compromise between CBR (constant bit rate) and VBR video coding. And its implementation is so simple that it could be easily utilized in on-line rate control for real-time video communication.
Comparison of second- and fourth-order cumulant-based MUSIC method in the presence of sensor errors
Authors: Liao Guisheng
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

We carry out a sensitivity analysis of fourth-order cumulant-based MUSIC method (FOC-MUSIC) via a generalized approach using a particular Taylor series expansion of a null spectrum function. We provide the variance of the estimate error for FOC-MUSIC with an emphasis on comparing robustness of FOC-MUSIC with that of the standard covariance matrix based MUSIC in the presence of sensor errors. We address the condition of effective aperture extension by higher-order cumulant-based processing, and give the new interpretation of effective aperture extension. A new fourth-order cumulants matrix is also given.
Learning style based innovations to improve retention of female engineering students in the Synthesis Coalition
Authors: A. M. Agogino, S. Hsi
Venue: Proceedings of the Frontiers in Education Conference, on 1995. Proceedings., 1995 - Volume 02 (1995)

The paper describes the use of integrative multimedia courseware designed to scaffold student learning and accommodate learning style differences. Synthesis courseware aimed at improving the retention of under-represented engineers has been further designed to work effectively in a range of educational settings, including classroom, high-tech small study groups and self-paced individualized learning. As an example, the paper focuses on the spatial reasoning project aimed at improving the retention of female engineering students through scaffolding students in spatial reasoning. The courseware described can be found on the NEEDS (National Engineering Delivery System) database of engineering courseware.
Computer self-efficacy and computer anxiety in a hospital social work and nursing case management department
Authors: Lorraine M. Gutierrez, John E. Tropman
Venue:  (2006)

The current health care delivery system increasingly relies upon information technology (IT) to more effectively and efficiently meet patient needs. The present study examined the relationship of computer self-efficacy, computer anxiety, and perceived computer usefulness to performance utilizing IT programs by clinical staff in a hospital-based social work and nursing case management department. Use of IT programs within the hospital setting was assessed by self-reported frequency of use of the shared drive system of electronic resources and by observed behavioral proficiency in completing a computerized search task of resources on the shared drive. Computer self-efficacy was assessed by a self-report survey adapted from the Computer Self-Efficacy Scale developed by Murphy, Coover, and Owen (1989). Computer anxiety was assessed by Johnson's (2005) self-report survey version of the Computer Anxiety Rating Scale adapted to reflect the specific IT programs utilized in the hospital setting. Computer usefulness was assessed by a modified version of the self-report Usefulness survey developed by Franz and Robey (1986). All of the 45 participants completed the self-report survey measures, with 27 also completing the computerized search task. An alpha level of .05 was used for all statistical tests. The results indicated significant relationships between observed behavioral proficiency on the computerized search task and self-reported ratings of computer self-efficacy and computer anxiety. Higher task proficiency was associated with higher computer self-efficacy ratings. Lower task proficiency was associated with higher computer anxiety. More frequent self-reported use of the shared drive system was significantly associated with higher ratings of computer usefulness.
Facial features localization in front view head and shoulders images
Authors: A. M. Alattar
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

The computerized process of locating human facial features such as the eyes, nose and mouth in a head and shoulders image is crucial to such applications as automatic face identification and model-based video coding. A new model-based algorithm for locating these major features is developed. The algorithm estimates the parameters of the ellipse which best fits the head view in the image and uses these parameters to calculate the estimated locations of the facial features. It then refines the estimated coordinates of the eyes, mouth, and nose by exploiting the vertical and horizontal projections of the pixels in windows around the estimated locations of the features. The algorithm has been implemented and tested with over twelve hundred images, and simulation results indicate that the algorithm is robust to variations in subject head shape, eye shape, age, and motion such as tilting and nodding of the head.
Confidence measures for the SWITCHBOARD database
Authors: S. Cox, R. Rose
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

There is increasing interest in systems which attempt to automate a task or a transaction using speech input and output. To function effectively with imperfect speech recognition, such systems require an estimate of which words in the output from the recogniser are likely to be correct and which can probably be disregarded as incorrect, i.e. a confidence-measure for each decoded word. We define a measure for evaluating the effectiveness of a post-classifier which estimates confidence-measures, and describe the development of a post-classifier for words decoded from the SWITCHBOARD database, which uses statistics derived from a Viterbi decoder. Without any grouping of the decoded word-classes, the post-classifier increased the probability of deciding whether a decoded word was correct or incorrect by 32%. When grouping was used, longer words showed an improvement of 65%.
Discrete–continuous and classical–quantum
Authors: Thierry Paul
Venue: Mathematical Structures in Computer Science (2007)

We present a discussion concerning the opposition between discreteness and the continuum in quantum mechanics. In particular, it is shown that this duality was not restricted to the early days of the theory, but remains current, and features different aspects of discretisation. In particular, the discreteness of quantum mechanics is key for quantum information and quantum computation. We propose a conclusion involving a concept of completeness linking discreteness and the continuum.
A novel rank-based classifier combination scheme for speaker identification
Authors: H. Altincay
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

In this paper, we propose a novel rank-based classifier combination scheme under uncertainty for speaker identification. The combination is based on a heuristic method that uses Dempster-Shafer theory of evidence under some conditions. The method is based on the extraction of first and R/sup th/ level ranking statistics. Using these statistics, the pattern classes are clustered into model sets where the classes in these sets share set specific properties. Some of these model sets are used to reflect the strengths and weaknesses where some others carry class dependent ranking statistics of the corresponding classifier. The experiments conducted on the Polycost database have shown that the proposed approach is more effective compared to some other rank-based combination schemes.
Software tool for transmission line analysis
Authors: E. Gago-Ribas
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 02 (2000)

A brief description of a software tool developed to analyze transmission lines with arbitrary losses is presented in this paper. This tool summarizes a complete methodology for the analysis of arbitrary transmission lines by means of complex parametrizations of the different quantities which characterize the line, and their mutual relationship. This kind of methodology brings up new types of representations and, in particular, new ways to visualize and predict the complete behavior of a particular system, avoiding the complexity associated to the usual mathematical representations. From the educational point of view, this approach facilitates a more intuitive and broad understanding of the problem, and the software tool lets the students to graphically visualize the physical behavior of the system.
Communal Detection of Implicit Personal Identity Streams
Authors: Clifton Phua, Ross Gayler, Kate Smith-Miles, Vincent Lee
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

The purpose of this paper is to outline some of the major developments of an identity crime/fraud stream mining system. Communal detection is about finding real communities of interest. The algorithm itself is unsupervised, single-pass, differentiates between normal and anomalous links, and mitigates the suspicion of normal links with a dynamic global whitelist. It is part of the important and novel communal detection framework introduced here for monitoring implicit personal identity streams. For each incoming identity example, it creates one of three types of single link (black, white, or anomalous) against any previous example within a set window. Subsequently, it integrates possible multiple links to produce a smoothed numeric suspicion score. In a principled stream-like fashion and using eighteen different parameter settings replicated over three large window sizes, this paper highlights and discusses significant score results from mining a few million recent credit applications.
Writing center programs for engineering
Authors: E. M. Alford
Venue: Proceedings of the 26th Annual Frontiers in Education - Volume 01 (1996)

Writing center programs encompass a variety of instructional and consultative services and provide effective approaches for integrating writing instruction into the engineering curriculum. A writing center program at the University of South Carolina's Department of Electrical and Computer Engineering (ECE) integrates both informal writing (writing-to-learn) and technical report writing instruction into the sequence of lab courses and senior level seminar courses. The ECE writing center program offers a structured program of individual consultations, group discussions, and team sessions to engage students in exploring discourse conventions of the field. These consultation processes encourage students to reflect on their experiences and guide engineering students in developing appropriate linguistic structures to communicate their findings in both written reports and in oral presentations. This presentation outlines steps for developing writing center programs in engineering, describing the collaboration necessary for successful operation and the research and assessment necessary for program effectiveness.
A Programmable Window Comparator for Analog Online Testing
Authors: Amit Laknaur, Rui Xiao, Haibo Wang
Venue: Proceedings of the 25th IEEE VLSI Test Symmposium (2007)

This paper discusses the challenge of designing window comparators for analog online testing applications. A programmable window comparator with adaptive error threshold is presented. Experimental results demonstrate that improved fault detection capability is achieved by using the proposed design. Measurement results of the fabricated comparator circuit are also presented.
Constructing two-weight codes with prescribed groups of automorphisms
Authors: Axel Kohnert
Venue: Discrete Applied Mathematics (2007)

We construct new linear two-weight codes over the finite field with q elements. To do so we solve the equivalent problem of finding point sets in the projective geometry with certain intersection properties. These point sets are in bijection to solutions of a Diophantine linear system of equations. To reduce the size of the system of equations we restrict the search for solutions to solutions with special symmetries. Two-weight codes can be used to define strongly regular graphs. We give tables of the two-weight codes and the corresponding strongly regular graphs. In some cases we find new distance-optimal two-weight codes and also new strongly regular graphs.
Figure-ground segmentation using a hierarchical conditional random field
Authors: Jordan Reynolds, Kevin Murphy
Venue: Proceedings of the Fourth Canadian Conference on Computer and Robot Vision (2007)

We propose an approach to the problem of detecting and segmenting generic object classes that combines three "off the shelf" components in a novel way. The components are a generic image segmenter that returns a set of "super pixels" at different scales; a generic classifier that can determine if an image region (such as one or more super pixels) contains (part of) the foreground object or not; and a generic belief propagation (BP) procedure for tree-structured graphical models. Our system combines the regions together into a hierarchical, tree-structured conditional random field, applies the classifier to each node (region), and fuses all the information together using belief propagation. Since our classifiers only rely on color and texture, they can handle deformable (non-rigid) objects such as animals, even under severe occlusion and rotation. We demonstrate good results for detecting and segmenting cows, cats and cars on the very challenging Pascal VOC dataset.
What impacts course evaluation?
Authors: Erik Larsson, Medhi Amirijoo, Daniel Karlsson, Petru Eles
Venue: ACM SIGCSE Bulletin (2007)

Today most universities are using course evaluations. However, course evaluations are often discussed and questioned. This paper reports on a survey where we aim at finding out (1) if students have a preconceived notion of a course, (2) if course evaluation scores can be predicted early in a course, (3) if exam throughput impacts course evaluation, and (4) if web-based evaluation reflects the general opinion from students. The results from the study indicate that students do not let preconceived notion impact nor does exam throughput matter to course evaluation. Further, the final web-based results seem to correlate with opinion of students attending lectures. However, the evaluation grades tend to be defined early in the course; hence first impression lasts.
Strategies for developing, implementing, and institutionalizing a comprehensive assessment process for engineering education
Authors: J. McGourty
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 01 (1998)

This paper draws upon experiences in the development and implementation of comprehensive educational assessment and continuous improvement programs in several US universities associated with the National Science Foundation's Gateway Coalition for Undergraduate Engineering Education. Four integrated strategies, required to imbed assessment and continuous improvement in the educational environment, are fully described.
Improved Resolution Scalability for Bi-Level Image Data in JPEG2000
Authors: Rahul Raguram, Michael W. Marcellin, Ali Bilgin
Venue: Proceedings of the 2007 Data Compression Conference (2007)

In this paper, we address issues regarding bi-level image compression using JPEG2000. While JPEG2000 is designed to compress both bi-level and continuous tone imagery using a single unified framework, there exist significant limitations with respect to its use in the lossless compression of bi-level imagery. In particular, substantial degradation in image quality at low resolutions severely limits the resolution scalable features of the JPEG2000 code-stream. We analyze these effects and present two efficient methods to improve resolution scalability for bi-level imagery in JPEG2000. It may be noted that both proposed methods are compliant with Part-I of the JPEG2000 standard.
The design of the dents DNS server
Authors: Todd Lewis
Venue: Proceedings of the annual conference on USENIX Annual Technical Conference (1999)

Dents is a server implementation of the Internet's Domain name System. Dents main features are a modular driver architecture, a CORBA-based control facility, a replaceable tree system, a clean design and good karma. Dents is free software, licensed under version 2 of the GPL. In this paper, I describe the design of Dents, concentrating on the innovations and evolutions it embodies, and including the future directions in which we hope to take the server. I describe some of the problems we've had. Finally, I summarize some lessons about server design which Dents reflects.
DRR-SFF: A Practical Scheduling Algorithm to Improve the Performance of Short Flows
Authors: Changhua Sun, Lei Shi, Chengchen Hu, Bin Liu
Venue: Proceedings of the Third International Conference on Networking and Services (2007)

Short flow first scheduling (SFF) strategy is effective in obtaining more stringent performance bounds for short flows in Internet. However, previous strict SFF approaches invested the short flows with excessive preference leading to the starvation of other long flows. Moreover, these SFFs are hard to be deployed due to either extreme complexity or the modification of TCP protocol. Inspired by the fairness and practicality of Deficit Round Robin (DRR), we proposed a novel scheduling mechanism, namely Deficit Round Robin with Short Flow First (DRR-SFF), which improves the performance of short flows with limited penalizing long flows. DRR-SFF uses Weighed DRR to schedule short and long flows respectively and treats long flows more fairly. Through trace-driven simulation, we show that the mean transmission time and loss rate of short flows under DRR-SFF are significantly reduced compared with FIFO scheduling using DropTail. Meanwhile, the performance of long flows under DRRSFF does not degrade much, retaining to that of FIFO scheduling. Our results demonstrate DRR-SFF is superior to strict SFF approaches, as the latter drives long flows into starvation in our simulations. Moreover, DRR-SFF inherits the O(1) computation complexity of DRR, which makes it easy to be deployed in edge routers.
Simulation and Analysis of Extended Brake Lights for Inter-Vehicle Communication Networks
Authors: Jason D. Watson, Mark Pellerito, Charlie Gladden, Huirong Fu
Venue: Proceedings of the 27th International Conference on Distributed Computing Systems Workshops (2007)

The goal of this research is to simulate and analyze an Inter-Vehicle Communication (IVC) Mobile Ad hoc Network (MANET). Automobiles of the future will take advantage of IVC capabilities, in which vehicles will communicate with one another wirelessly. The Crash Avoidance Metrics Partnership (CAMP) Vehicle Safety Communications Consortium (VSCC) has identified three scenarios that are representative of the capabilities of future vehicular networks: Curve Speed Warning (CSW), Traffic Signal Violation Warning (TSVW), and Extended Brake Lights (EBL). We consider only EBL, as it is the only scenario that involves direct communication between vehicles. This research aims to simulate the EBL scenario over an IVC network, and analyze the network using accepted metrics and benchmarks. The resulting performance data may influence and motive future research efforts.
A Robust Lightweight Solution for RFID Security
Authors: Anahita Vyas, Sheikh I. Ahamed, Munirul M. Haque, Madhavi V. S. Jayanthi
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

The ubiquitous adoption of RFID technology is becoming integral part of our life. The stringent behavior of RFID system makes it more prone to impendence situations. Consequently, it needs more enduring and testing to become less susceptible to attacks without compromising the crucial key factors like, memory, cost, speed, computation and handling. An approach without concerning all these factors is not an acceptable approach. In this paper, we present a more persistent solution that provides security without compromising the crucial key factors and addressing all security issues like eavesdropping, tracking, cloning and replay attacks.
Monte Carlo Methods in PageRank Computation: When One Iteration is Sufficient
Authors: K. Avrachenkov, N. Litvak, D. Nemirovsky, N. Osipova
Venue: SIAM Journal on Numerical Analysis (2007)

PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer, and thus it reflects the popularity of a Web page. Google computes the PageRank using the power iteration method, which requires about one week of intensive computations. In the present work we propose and analyze Monte Carlo-type methods for the PageRank computation. There are several advantages of the probabilistic Monte Carlo methods over the deterministic power iteration method: Monte Carlo methods already provide good estimation of the PageRank for relatively important pages after one iteration; Monte Carlo methods have natural parallel implementation; and finally, Monte Carlo methods allow one to perform continuous update of the PageRank as the structure of the Web changes.
Fractionally-spaced constant modulus algorithm blind equalizer error surface characterization: effects of source distributions
Authors: J. P. LeBlanc
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

The constant modulus algorithm (CMA) is a popular blind equalization algorithm. A common device used in demonstrating the convergence properties of CMA is the assumption that the source sequence is i.i.d. (independent, identically distributed). Previous results in the literature show that a finite length fractionally-spaced equalizer allows for perfect equalization of moving average channels (under certain channel conditions known as zero-forcing criteria). CMA has previously been shown to converge to such perfectly equalizing settings under an independent, platykurtic source. This paper investigates the effect of the distribution from which an independent source sequence is drawn on the CMA error surface and stationary points in the perfectly-equalizable fractionally-sampled equalizer case. Results include symbolic identification of all stationary points, as well as the eigenvalues and eigenvectors associated with their Hessian matrix. Results show quantitatively the loss of error surface curvature (in both direction and magnitude) at all stationary points. Simulations included demonstrate the affect this has on convergence speed.