ppxscal/embedding_network huggingface dataset:
Codeword quantization for interference avoidance
Authors: D. C. Popescu
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

Programmable radios offer a new perspective on wireless communications since the modulation method is no longer fixed. Adaptive methods where user signatures and corresponding receiver filters are iteratively adapted can be used to improve performance. However, since codeword adjustments must be fed back to the transmitter, compact representation of codewords is extremely important. This issue is important for systems which employ interference avoidance since as opposed to current CDMA systems where uniform-amplitude codeword chips are used, interference avoidance employs real-valued "chips"-real-valued coefficients for a set of orthonormal basis functions of the signal space used by the transmitter and receiver. The paper represents a simple investigation of how codeword quantization affects the performance of interference avoidance algorithms. Results indicate that using 4-5 bits per chip for codeword representation is sufficient to maintain performance close to optimal values.
Toward the Use of Automated Static Analysis Alerts for Early Identification of Vulnerability- and Attack-prone Components
Authors: Michael, Laurie Williams
Venue: Proceedings of the Second International Conference on Internet Monitoring and Protection (2007)

Extensive research has shown that software metrics can be used to identify fault- and failure-prone components. These metrics can also give early indications of overall software quality. We seek to parallel the identification and prediction of fault- and failure-prone components in the reliability context with vulnerability- and attack-prone components in the security context. Our research will correlate the quantity and severity of alerts generated by source code static analyzers to vulnerabilities discovered by manual analyses and testing. A strong correlation may indicate that automated static analyzers (ASA), a potentially early technique for vulnerability identification in the development phase, can identify high risk areas in the software system. Based on the alerts, we may be able to predict the presence of more complex and abstract vulnerabilities involved with the design and operation of the software system. An early knowledge of vulnerability can allow software engineers to make informed risk management decisions and prioritize redesign, inspection, and testing efforts. This paper presents our research objective and methodology.
Sound analysis using MPEG compressed audio
Authors: G. Tzanetakis
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

There is a huge amount of audio data available that is compressed using the MPEG audio compression standard. Sound analysis is based on the computation of short time feature vectors that describe the instantaneous spectral content of the sound. An interesting possibility is the calculation of features directly from compressed data. Since the bulk of the feature calculation is performed during the encoding stage this process has a significant performance advantage if the available data is compressed. Combining decoding and analysis in one stage is also very important for audio streaming applications. In this paper, we describe the calculation of features directly from MPEG audio compressed data. Two of the basic processes of analyzing sound are: segmentation and classification. To illustrate the effectiveness of the calculated features we have implemented two case studies: a general audio segmentation algorithm and a music/speech classifier. Experimental data is provided to show that the results obtained are comparable with sound analysis algorithms working directly with audio samples.
Distance teaming experiments in undergraduate DSP
Authors: D. M. Etter
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

This paper describes the ongoing efforts of the participants of the Signal Processing Education consortium (SPEC) in bringing the most up-to-date technologies to the teaching of undergraduate digital signal processing. In particular, we describe herein the use of new multimedia technologies for distributed teaming of undergraduates and faculty to both take advantage of the diverse faculty expertise and to mimic the increasingly common practice of distributed teaming in industry.
Embedding New IT Artifacts into Design Practice for Knowledge Creation
Authors: Ryan Baxter, Nicholas Berente
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

Designers create knowledge through interaction with artifacts in their environment. Information systems literature addresses how IT artifacts are embedded in practice, and how new IT artifacts are accepted and adapted. However, there is little attention to the processes that enable new IT artifacts to become embedded in practice when existing IT artifacts are already entrenched in design activity. Knowledge-creating design practice involves intimate cognitive relationships between designers and artifacts, and it is no trivial task to migrate invested knowledge from existing artifacts that are embedded in practice to new artifacts which take time to master in order to create knowledge. Using an in-depth case study of Frank Gehry, a world-renown and radically innovative architect, we illustrate four phenomena associated with the embedding of a new, fundamentally more complex computer-aided design system into the practice of designers: (1) motivating the new artifact; (2) anchoring the new artifact in the old; (3) building trust in the new artifact; (4) unlearning past practices.
Proportional-share scheduling for distributed storage systems
Authors: Yin Wang, Arif Merchant
Venue: Proceedings of the 5th USENIX conference on File and Storage Technologies (2007)

Fully distributed storage systems have gained popularity in the past few years because of their ability to use cheap commodity hardware and their high scalability. While there are a number of algorithms for providing differentiated quality of service to clients of a centralized storage system, the problem has not been solved for distributed storage systems. Providing performance guarantees in distributed storage systems is more complex because clients may have different data layouts and access their data through different coordinators (access nodes), yet the performance guarantees required are global. This paper presents a distributed scheduling framework. It is an adaptation of fair queuing algorithms for distributed servers. Specifically, upon scheduling each request, it enforces an extra delay (possibly zero) that corresponds to the amount of service the client gets on other servers. Different performance goals, e.g., per storage node proportional sharing, total service proportional sharing or mixed, can be met by different delay functions. The delay functions can be calculated at coordinators locally so excess communication is avoided. The analysis and experimental results show that the framework can enforce performance goals under different data layouts and workloads.
The Center for Computational Science and Engineering at the U.S. Naval Academy
Authors: P. R. Turner
Venue: Proceedings of the Frontiers in Education Conference, 2001. 31st Annual - Volume 02 (2001)

There is a strong and increasing desire for more multidisciplinary activities within mathematical, scientific and engineering education. This has found particularly strong voice in the rise of graduate programs in Computational Science and Engineering. The growth of such programs and centers is only just beginning to take root in the undergraduate curriculum. In this paper, the authors describe the proposal, founding and development of a Center for CSE at an undergraduate school. The center grew from an initial proposal to planning and running its first multidisciplinary course in one year. In the paper, they describe the chronology of this process as well as giving some pointers on how to go about creating the right environment for such a development in undergraduate colleges. The development of a special team-taught multidisciplinary course is also described.
Montage: an ActiveX container for dynamic interfaces
Authors: Gordon Woodhull, Stephen C. North
Venue: Proceedings of the 2nd conference on USENIX Windows NT Symposium - Volume 2 (1998)

Montage is a customizable, embeddable ActiveX container. Its client objects may be positioned dynamically by an external layout agent. Montage manages toolbars and user interface modes, integrating disparate components into a single, consistent interface. An important part of this task is supporting "group repositories" of related objects for data transfer operations such as cut-and-paste, drag-and-drop, save and load. Montage does not rely on large external libraries such as the Microsoft Foundation Classes, and thus is relatively lightweight. The prototypical Montage application is an embeddable display for dynamic networks (abstract graphs).
A Compound and Robust Algorithm for Ellipse Detection
Authors: Mao Jianfei, Xiong Rong, Ding Weilong
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

Aiming for ellipse detection in complex environment, we propose a compound algorithm. In the scene image that we see everyday, there are usually many corner points and straight lines and it is not practical to use Randomized Hough Transform (RHT) to detect ellipse from such an image, for that the corner points and straight lines everywhere bring numerous noneffective samplings and accumulatings. Aiming at the solution of the problem, we firstly filter noisy points, corner points and straight lines, as many noneffective samplings are eliminated, then we use a compound ellipse detection algorithm to detect ellipse. Firstly use all points of the curve to fit ellipse by least squares and judge if it is the right ellipse, if not, sample five points random from the curve to solve the ellipse parameters, then an effective ellipse fitting rule is proposed to judge whether a point belongs to the solved ellipse. We use the above random sampling and ellipse fitting rule repetitiously to find the most fitting ellipse. In above processing we make full use of the continuity of the edge to sample points random and fit ellipse, as it reduces much more noneffective samplings and accumulatings. Simulation and experiments indicate that this algorithm is more robust and faster than RHT.
A framework for automating human identification using dental x-ray radiographs
Authors: Mohamed Abdel-Mottaleb
Venue:  (2006)

Law enforcement agencies have been exploiting biometric identifiers for decades as key tools in forensic identification. With the evolution in information technology and the huge volume of cases that need to be investigated by forensic specialists, it has become important to automate forensic identification systems. While ante mortem (AM) identification, i.e., identification prior to death, is usually possible through comparison of many biometric identifiers; postmortem (PM) identification, i.e., identification after death, is impossible using behavioral biometrics (e.g. speech, gait). Moreover, under severe circumstances, such as those encountered in mass disasters (e.g. airplane crashers) or if identification is being attempted more than a couple of weeks postmortem, most physiological biometrics may not be employed for identification, because of the decay of soft tissues of the body to unidentifiable states. Therefore, a postmortem biometric identifier has to resist the early decay that affects body tissues. Because of their survivability and diversity, the best candidates for postmortem biometric identification are the dental features. Forensic odontology is the branch of forensics that deals with human identification based on dental features. In this dissertation, we present a system for automating that process by identifying people from dental X-ray images. Given a dental image of a postmortem (PM), the proposed system retrieves the best matches from an antemortem (AM) database. The system automatically segments dental X-ray images into individual teeth and extracts representative feature vectors for each tooth; which are later used for retrieval. We developed a new method for teeth segmentation; and three different methods for representing and matching teeth. Each method has a different technique for representing the tooth shape and has its advantages and disadvantages compared with the other methods. The first method represents each tooth contour by signature vectors obtained at salient points on the contour of the tooth. The second method uses Hierarchical Chamfer distance for matching AM and PM teeth. In the third method, each tooth is described using a feature vector extracted using the force field energy function and Fourier descriptors. During retrieval, according to a matching distance between the AM and PM teeth, AM radiographs that are most similar to a given PM image, are found and presented to the user. To increase the accuracy of the identification process, the three matching techniques are fused together. The fusion of information is an integral part of any identification system to improve the overall performance. We introduce some scenarios for fusing the three matchers at the score level as well as at the fusion level.
Optimal Source-Channel Decoder for Correlated Markov Sources over Additive Markov Channels
Authors: M. A. Haleem, K. P. Subbalakshmi
Venue: Proceedings of the 2007 Data Compression Conference (2007)

In this paper we propose an optimal joint source channel decoder (JSCD) for two mutu- ally correlated sources each having memory that can be represented by ¯rst order Markov processes, and are transmitted through channels with memory representing slow fading wireless channels. We use the additive markov channel (AMC) model and multiple access source codes (MASC).
Joint Optimization of Distributed Broadcast Quantization Systems for Classification
Authors: Michael A. Lexa, Don H. Johnson
Venue: Proceedings of the 2007 Data Compression Conference (2007)

We develop a simulated annealing technique to jointly optimize a distributed quantiza- tion structure meant to maximize the asymptotic error exponent of a downstream classifier or detector. This distributed structure sequentially processes an input vector and exploits broadcasts to improve the best possible error exponents. The annealing approach is a robust technique that avoids local maxima and is easily tailored to a broadcast quantizer's structural constraints.
What do faculty need and want from digital libraries?
Authors: Flora P. McMartin, Alan Wolf, Ellen Iverson, Cathrynn Manduca, Glenda Morgan, Joshua Morrill
Venue: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries (2007)

In this paper, we report on the results of a national survey of faculty members concerning their use of digital resources (DRs), collections of resources and digital libraries (DLs). The research reported here explored issues such as: value of DRs, motivation for using DRs and barriers to use of these resources in teaching. The results have implications for how DLs might develop education and outreach efforts to increase visibility and use of their collections.
The fractional spline wavelet transform: definition end implementation
Authors: T. Blu
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

We define a new wavelet transform that is based on a previously defined family of scaling functions: the fractional B-splines. The interest of this family is that they interpolate between the integer degrees of polynomial B-splines and that they allow a fractional order of approximation. The orthogonal fractional spline wavelets essentially behave as fractional differentiators. This property seems promising for the analysis of 1/f/sup /spl alpha// noise that can be whitened by an appropriate choice of the degree of the spline transform. We present a practical FFT-based algorithm for the implementation of these fractional wavelet transforms, and give some examples of processing.
Joint throughput and energy optimization for pipelined execution of embedded streaming applications
Authors: Po-Kuan Huang, Matin Hashemi, Soheil Ghiasi
Venue: Proceedings of the 2007 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems (2007)

We present a methodology for synthesizing streaming applications, modeled as task graphs, for pipelined execution on multi-core architectures. We develop a task graph extraction and characterization framework that accurately determines the structure, computation and communication characteristics of application task graph from its specification in C. Furthermore, we develop a provably optimal algorithm that jointly balances the workload assigned to each core, and minimizes inter-core communication traffic. Experiment results show that our versatile method improves the through-put of streaming applications significantly under a variety of hardware configurations.
Towards a robust real-time decoder
Authors: J. Davenport
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

We present several algorithms that speed up our BBN BYBLOS decoder. We briefly describe the techniques that we have used before this year. Then we present new techniques that speed up the recognition search by a factor of 10 with little effect on accuracy using a combination of fast Gaussian computation, grammar spreading, and grammar caching, within the 2-pass n-best paradigm. We also describe our decoder metering strategy, which allows us to conveniently test for search errors. Finally, we describe a grammar compression technique that decreases the storage needed for each additional ngram to only 10 bits.
Data reduction for the scalable automated analysis of distributed darknet traffic
Authors: Michael Bailey, Evan Cooke, Farnam Jahanian, Niels Provos, Karl Rosaen, David Watson
Venue: Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement (2005)

Threats to the privacy of users and to the availability of Internet infrastructure are evolving at a tremendous rate. To characterize these emerging threats, researchers must effectively balance monitoring the large number of hosts needed to quickly build confidence in new attacks, while still preserving the detail required to differentiate these attacks. One class of techniques that attempts to achieve this balance involves hybrid systems that combine the scalable monitoring of unused address blocks (or darknets) with forensic honeypots (or honeyfarms). In this paper we examine the properties of individual and distributed darknets to determine the effectiveness of building scalable hybrid systems. We show that individual darknets are dominated by a small number of sources repeating the same actions. This enables source-based techniques to be effective at reducing the number of connections to be evaluated by over 90%. We demonstrate that the dominance of locally targeted attack behavior and the limited life of random scanning hosts result in few of these sources being repeated across darknets. To achieve reductions beyond source-based approaches, we look to source-distribution based methods and expand them to include notions of local and global behavior. We show that this approach is effective at reducing the number of events by deploying it in 30 production networks during early 2005. Each of the identified events during this period represented a major globally-scoped attack including the WINS vulnerability scanning, Veritas Backup Agent vulnerability scanning, and the MySQL Worm.
Blind signal separation for convolutive mixing environments using spatial-temporal processing
Authors: J. P. Reilly
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

In this paper we extend the infomax technique of Bell and Sejnowski (see Neural Computation, vol.7, no.6, p.1129-59, 1995) for blind signal separation from the instantaneous mixing case to the convolutive mixing case. Separation in the convolutive case requires an unmixing system which uses present and past values of the observation vector, when the mixing system is causal. Thus, in developing an infomax process, both temporal and spatial dependence of the observations must be considered. We propose a stochastic gradient based structure which accomplishes this task. The performance of the proposed method is verified by subjective listening tests and quantitative measurements.
Proposal of Constructing PKI on Overlay Network
Authors: Yukio Okada, Hiroaki Hazeyama, Youki Kadobayashi
Venue: Proceedings of the 2007 International Symposium on Applications and the Internet Workshops (2007)

In this paper, we present the design of foundation PKI (fPKI), a PKI system constructed on an overlay network for an open source community. fPKI can provide an alternative PKI system to the current server-client PKI system. The Certificate Authority (CA) system of the fPKI is composed of the reputation of each committer, which has been assessed by the SecureEigenTrust[4] algorithm. fPKI inherits the scalability of SecureEigenTrust, and also inherits the common CA usage of the server-client PKI system.
The imagination market
Authors: Christina Ann Lacomb, Janet Arlie Barnett, Qimei Pan
Venue: Information Systems Frontiers (2007)

Information markets are typically used as prediction tools, aggregating opinions about the likelihood of future events, or as preference indicators, identifying participants' product preferences. However, the basic information market concept is more widely applicable. In our experiment, we utilized information markets within the domains of idea generation and group decisioning. Participants were allowed to propose ideas regarding potential technology research areas; these ideas were represented as securities on a virtual financial market. Participants were able to trade shares of technology ideas over the course of 3 weeks, resulting in the market identifying the "best" idea as the highest priced security. Our findings suggest that information markets for idea generation result in more ideas and more participants than traditional idea generation techniques; however, using markets to rank ideas may be no better than other methods of idea ranking. Additional benefits include providing immediate feedback, allowing visibility of all ideas to all contributors, and being a fun mechanism for consensus building.
Embedding Grids, Hypercubes, and Trees in Arrangement Graphs
Authors: Khaled Day, Anand Tripathi
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 03 (1993)

The use of a new topology, called the arrangement graph, as a viable interconnection scheme for parallel and distributed systems, has been recently proposed and examined. The arrangement graphs represent a rich class of generalized star graphs with many attractive properties, In this paper we obtain (1) unit expansion embeddings of a variety of multi-dimensional grids, (2) dilation 1, 2, 3, and 4 embeddings of hypercubes and (3) hierarchical and greedy spanning trees to support broadcasting and personalized communication in arrangement graphs.