ppxscal/embedding_network huggingface dataset:
Public Key Management Framework for Two-tier Super Peer Architecture
Authors: Hyeokchan Kwon, Sangchoon Kim, Jaehoon Nah, Jongsoo Jang
Venue: Proceedings of the 27th International Conference on Distributed Computing Systems Workshops (2007)

Many internet applications use public key infrastructure (PKI) to enable the secure transaction of confidential messages. However, the use of PKI is not consistent with the ideas of peer-to-peer networks. In this paper, we propose public key management framework to distribute public key safely without PKI infrastructure for two-tier super peer architecture. In this framework, each peer self-generates and distributes public/private key pairs. In general case, this kind of mechanism is vulnerable to man-in-themiddle attack during the public key distribution process. But the proposed mechanism can easily avoid this kind of attack.
Sentence level information patterns for novelty detection
Authors: W. Bruce Croft
Venue:  (2006)

The detection of new information in a document stream is an important component of many potential applications. In this thesis, a new novelty detection approach based on the identification of sentence level information patterns is proposed. Given a user's information need, some information patterns in sentences such as combinations of query words, sentence lengths, named entities and phrases, and other sentence patterns, may contain more important and relevant information than single words. The work of the thesis includes three parts. First, we redefine "what is novelty detection" in the lights of the proposed information patterns. Examples of several different types of information patterns are given corresponding to different types of uses' information need. Second, we analyze why the proposed information pattern concept has a significant impact in novelty detection. A thorough analysis of sentence level information patterns is elaborated on data from the TREC novelty tracks, including sentence lengths, named entities (NEs), and sentence level opinion patterns. Finally, we present how we perform novelty detection based on information patterns, which focuses on the identification of previously unseen query-related patterns in sentences. A unified pattern-based approach is presented to novelty detection for both specific NE topics and more general topics. Experiments on novelty detection were carried out on data from the TREC 2002, 2003 and 2004 novelty tracks. Experimental results show that the proposed approach significantly improves the performance of novelty detection for both specific and general topics, therefore the overall performance for all topics, in terms of precision at top ranks. Future research directions are suggested.
Security-driven scheduling for data-intensive applications on grids
Authors: Tao Xie, Xiao Qin
Venue: Cluster Computing (2007)

Security-sensitive applications that access and generate large data sets are emerging in various areas including bioinformatics and high energy physics. Data grids provide such data-intensive applications with a large virtual storage framework with unlimited power. However, conventional scheduling algorithms for data grids are unable to meet the security needs of data-intensive applications. In this paper we address the problem of scheduling data-intensive jobs on data grids subject to security constraints. Using a security- and data-aware technique, a dynamic scheduling strategy is proposed to improve quality of security for data-intensive applications running on data grids. To incorporate security into job scheduling, we introduce a new performance metric, degree of security deficiency, to quantitatively measure quality of security provided by a data grid. Results based on a real-world trace confirm that the proposed scheduling strategy significantly improves security and performance over four existing scheduling algorithms by up to 810% and 1478%, respectively.
Multiple classifiers by constrained minimization
Authors: P. Niyogi
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

The paper describes an approach to combining multiple classifiers in order to improve classification accuracy. Since individual classifiers in the ensemble should somehow be uncorrelated to yield higher classification accuracy than a single classifier, we propose to train classifiers by minimizing the correlation between their classification errors. A simple combination strategy for three classifiers is then proposed and its achievable error rate is analyzed and compared to individual single classifier performance. The proposed approach has been evaluated on artificial data and a nasal/oral vowel classification task. Theoretical analyses and experimental results illustrate the effectiveness of the proposed approach.
Region-adaptive motion tracking of speckle imagery
Authors: E. S. Ebbini
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

A new algorithm for speckle tracking is introduced. The algorithm is based on 2D correlation processing of beamformed radio frequency (RF) data from a medical imaging scanner employing a linear array of transducers. However, it is based on two powerful features for mask size design and for optimizing search direction for efficient implementation. An eigenvalue decomposition of a local intraframe spatial correlation matrix is used to determine the mask size. In addition, the search direction is determined from the 2D gradiant of the phase profiles of an interframe spatial correlation matrix. The result is a robust and computationally efficient speckle tracking algorithm suitable for medical imaging applications. A description of the new algorithm is given in this paper along with illustrative examples from image sequences obtained from tissue mimicking phantoms and in vivo liver images from a healthy volunteer. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A weighted linear prediction approach for the blind CDMA forward link channel estimation
Authors: S. Houcke
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

Blind channel estimation for periodic sequence DS-CDMA systems can be cast into the framework of "structured" blind estimation of multi-input/multi-output (MIMO) FIR systems, where the structure is imposed by the user's signatures. The well known subspace method can in particular be adapted to this context, but it suffers from a lack of robustness to an over-determination of the order of the channel. In a previous work, we showed that the use a structured linear prediction approach can overcome this drawback. However, the statistical performance of the corresponding estimate are disappointing. In this paper, we concentrate on the forward link channel estimation, and propose to use a weighted linear prediction approach. The optimal weighting matrix is in practice quite difficult to use. We therefore propose a sub-optimum matrix, leading to a quite simple estimation algorithm, and which is shown to have optimum performance when the signal to noise ratio converges to +/spl infin/. Some simulation results confirm the potential of the new approach.
Retrieval of Spatial Join Pattern Instances from Sensor Networks
Authors: Man Lung Yiu, Nikos Mamoulis, Spiridon Bakiras
Venue: Proceedings of the 19th International Conference on Scientific and Statistical Database Management (2007)

We study the continuous evaluation of spatial join queries and extensions thereof, defined by interesting combinations of sensor readings (events) that co-occur in a spatial neighborhood. An example of such a pattern is "a high temperature reading in the vicinity of at least four high-pressure readings". We devise acquisitional and distributed protocols for evaluating this class of queries, aiming at the minimization of energy consumption. Cases of simple and complex join queries with single or multi-hop distance constraints are considered. Finally, we experimentally compare the effectiveness of the proposed solutions on an experimental platform that simulates real sensor networks. Our results show that acquisitional protocols perform best for multi-hop or high-selectivity queries while distributed techniques should be applied for the remaining cases.
Gabor Wavelet Based Modular PCA Approach for Expression and Illumination Invariant Face Recognition
Authors: Neeharika Gudur, Vijayan Asari
Venue: Proceedings of the 35th Applied Imagery and Pattern Recognition Workshop (2006)

A Gabor wavelet based Modular PCA approach for face recognition is proposed in this paper. The proposed technique improves the efficiency of face recognition, under varying illumination and expression conditions for face images when compared to traditional PCA techniques. In this algorithm the face images are divided into smaller sub-images called modules and a series of Gabor wavelets at different scales and orientations are applied on these localized modules for feature extraction. A modified PCA approach is then applied for dimensionality reduction. Due to the extraction of localized features using Gabor wavelets, the proposed algorithm is expected to give improved recognition rate when compared to other traditional techniques. The performance of the proposed technique is evaluated under conditions of varying illumination, expression and variation in pose up to a certain range using standard face databases.
The Knowledge Grid Based Intelligent Electronic Commerce Recommender Systems
Authors: Pingfeng Liu, Guihua Nie, Donglin Chen, Zhichao Fu
Venue: Proceedings of the IEEE International Conference on Service-Oriented Computing and Applications (2007)

Centralized recommender systems can not resolve the contradiction between high recommendation quality and timely response, as well as that between limited recommendation range and ever rich information on the web. Distributed recommender systems are expected to improve the recommendation quality while maintaining high performance. Large-scale distributed recommendation involves the coordination of various heterogeneous resources which are located on different nodes and need to be represented uniformly and organized normally into the resource space so that a semantically interactive environment can be formed. In this paper the recommendation task is defined as a knowledge based workflow and the knowledge grid is exploited as the platform for knowledge sharing and knowledge service which provides the functions of knowledge discovery, knowledge fusion and knowledge based workflow definition. The rationale of the knowledge grid based intelligent electronic recommender systems (KGBIECRS) is discussed and the service oriented architecture of the knowledge grid is presented. The knowledge grid depends on the semantic grid as the semantically interactive platform to intelligently coordinate the heterogeneous resources on the grid so that the recommendation task submitted by the knowledge grid as a knowledge based workflow can be performed intelligently and adaptively. How to implement the system is also discussed. Finally an example of travel recommendation is given to elaborate the recommendation process.
A network of Kalman filters for MAP symbol-by-symbol equalization
Authors: R. Amara
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

A network of Kalman filters (NKF) has been proposed for the equalization of digital communication channels. The NKF-based equalizer relies on the approximation of the a posteriori probability density function (PDF) of a sequence of delayed symbols by a Weighted Gaussian Sum (WGS). The problem is that the number of Gaussian terms in the sum increases dramatically through iterations and thus, is not practical for an on-line processing. We propose a modified NKF-based equalizer which consists in replacing the WGS by a Gaussian density minimizing a certain quadratic criterion. We show that this later is centered on the MAP estimate of the sequence of symbols. The resulting modified NKF-based equalizer is shown to have improved performance and is compared to the optimal MAP symbol-by-symbol equalizer (MAPSE).
Improving web server performance by caching dynamic data
Authors: Arun Iyengar, Jim Challenger
Venue: Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems (1997)

Dynamic Web pages can seriously reduce the performance of Web servers. One technique for improving performance is to cache dynamic Web pages. We have developed the Dynamic Web cache which is particularly well-suited for dynamic pages. Our cache has improved performance significantly at several commercial Web sites. This paper analyzes the design and performance of the DynamicWeb cache. It also presents a model for analyzing overall system performance in the presence of caching. Our cache can satisfy several hundred requests per second. On systems which invoke server programs via CGI, the DynamicWeb cache results in near-optimal performance, where optimal performance is that which would be achieved by a hypothetical cache which consumed no CPU cycles. On a system we tested which invoked server programs via ICAPI which has significantly less overhead than CGI, the DynamicWeb cache resulted in near-optimal performance for many cases and 58% of optimal performance in the worst case. The DynamicWeb cache achieved a hit rate of around 80% when it was deployed to support the official Internet Web site for the 1996 Atlanta Olympic games.
Public-Key Cryptography for RFID-Tags
Authors: L. Batina, J. Guajardo, T. Kerins, N. Mentens, P. Tuyls, I. Verbauwhede
Venue: Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications Workshops (2007)

RFID-tags are a new generation of bar-codes with added functionality. An emerging application is the use of RFID-tags for anti-counterfeiting by embedding them into a product. Public-key cryptography (PKC) offers an attractive solution to the counterfeiting problem but whether a publickey cryptosystem can be implemented on an RFID tag or not remains unclear. In this paper, we investigate which PKC-based identification protocols are useful for these anti-counterfeiting applications. We also discuss the feasibility of identification protocols based on Elliptic Curve Cryptography (ECC) and show that it is feasible on RFID tags. Finally, we compare different implementation options and explore the cost that side-channel attack countermeasures would have on such implementations.
Sparse approximations for high fidelity compression of network traffic data
Authors: William Aiello, Anna Gilbert, Brian Rexroad, Vyas Sekar
Venue: Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement (2005)

An important component of traffic analysis and network monitoring is the ability to correlate events across multiple data streams, from different sources and from different time periods. Storing such a large amount of data for visualizing traffic trends and for building prediction models of "normal" network traffic represents a great challenge because the data sets are enormous. In this paper we present the application and analysis of signal processing techniques for effective practical compression of network traffic data. We propose to use a sparse approximation of the network traffic data over a rich collection of natural building blocks, with several natural dictionaries drawn from the networking community's experience with traffic data. We observe that with such natural dictionaries, high fidelity compression of the original traffic data can be achieved such that even with a compression ratio of around 1:6, the compression error, in terms of the energy of the original signal lost, is less than 1%. We also observe that the sparse representations are stable over time, and that the stable components correspond to well-defined periodicities in network traffic.
Separating wheat from the chaff: a deployable approach to counter spam
Authors: Youngsang Shin, Minaxi Gupta, Rob Henderson, Aaron Emigh
Venue: Proceedings of the 2nd conference on Steps to Reducing Unwanted Traffic on the Internet - Volume 2 (2006)

Unsolicited bulk email, aka spam is a persistent threat to the usefulness of the Internet. The fight against spam today relies solely on filtering at the recipient's mail server, which can delay mail delivery. We present a spam countering approach consisting of two complementary techniques. The first, token-based authentication, can identify emails from valid senders that a user expects to hear from. This identification prevents much of the good mail from being subjected to the filtering process. The second technique, history-based prioritization, is designed for the rest of the email. It utilizes past information about the sending mail servers and their domains to prioritize email filtration, thus reducing delays in the delivery of good email over spam. The proposed techniques do not rely on any infrastructure, deployed or otherwise, and any mail server can choose to deploy them independent of the choice made by the any other mail server.
Improving Remote Accessibility of Spatial Data
Authors: Mingyuan Yu
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

In recent years, many GIS applications have appeared on the Web giving users access to both spatial and non-spatial (attribute) data. However, a challenging task of Vector Active Map formats with such large volumes of online spatial data is that, in order to display them in most web browsers, either a plug-in has to be installed or an applet has to be downloaded. In this paper, a web service is proposed whose functionality enables the transformation of vector active maps from SVG to a new DHTML Active Map Representation, improving remote accessibility of spatial data. This new representation includes a raster representation of the map and a vector representation of its geographic objects. The former is used as a background image of the map whereas the latter enables the response to user-triggered events. A multi-level R-tree spatial index structure is used to access the geographic objects affected by each event in order to execute the relevant action.
Circularly symmetric watermark embedding in 2-D DFT domain
Authors: V. Solachidis
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

This paper presents an algorithm for rotation and scale invariant watermarking of digital images. An invisible mark is embedded in magnitude of the DFT domain. It is robust to compression, filtering, cropping, translation and rotation. The watermark introduces image changes that are invisible to the human eye. The detection algorithm does not require the original image.
Deformable Registration using Spring Mass System with Cross-section Correction
Authors: Jian-Kun Shen, Bogdan J. Matuszewski, Lik-Kwan Shark, Christopher J. Moore
Venue: Proceedings of the International Conference on Medical Information Visualisation - BioMedical Visualisation (2007)

When applying 2D deformable registration to crosssectional images from 3D data, it is assumed the images represent the same object. However, in reality, they are acquired at different axial positions and with different coronal and sagittal rotations. Therefore, if the crosssection's position and orientation can be corrected, it should offer better registration accuracy. The paper describes a "2.5D" method for correcting position and orientation of the cross-section under the in-plane 2D deformable registration. For a given source image, the algorithm estimates the optimal position and orientation of the cross-section generating target image as well as displacement field of the source image. For in-plane 2D deformable registration, a previously proposed method is being used. It models the deformations using a spring mass system, which contains a number of sparse masses interconnected by springs. The external forces calculated from the image contents are used to iteratively guide the system to the "good" matching configuration under the constraints imposed by the internal forces. The performance of the method is tested using real Radiation Therapy Planning CT (RTPCT) and Cone Beam CT (CBCT) as well as the simulated data. The results indicate that the newly proposed method improves registration accuracy.
Process, Knowledge, Touchpoints in Mental Health Communities of Practice
Authors: Ivor F. Perry
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

This paper takes as its starting point the paradox of process and care in a mental health setting. On the one hand, a number of "care pathways' can be defined and employed, to ease the administrative and logistical burden of caring for mentally ill patients. On the other hand, the highly individualized interaction with the patient demands constant knowledge "refreshment' and frequent knowledge creation that does not sit easily with re-iterative processes. The paper considers the options for process-based systems as "assistants' to professional staff, and considers the extent to which such systems can complement or manage types of tacit knowledge, such as "know-how' or emotion. A grounded theory approach and discourse analysis were used to obtain data for an exploratory study
Analyzing the real-time behaviour of deeply embedded event driven systems
Authors: Karsten Walther, René Herzog, Jörg Nolte
Venue: Proceedings of the 2007 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems (2007)

Most embedded control systems react on events in the real world by reading sensors and controlling actuators in real-time. This general behavior can be directly mapped onto event-driven systems in a natural and straightforward manner for a large variety of applications. Further real-time analysis and profiling on the same level of abstraction is possible for event-driven systems. This significantly helps developers of deeply embedded real-time applications. In this paper we introduce simulative profiling concepts and static analysis basics for the real-time analysis of event-driven systems. Furthermore we present a prototype analysis tool for the REFLEX operating system that integrates real-time analysis into the software development cycle.
A Novel Algorithm for Estimating Vehicle Speed from Two Consecutive Images
Authors: Xiao Chen He, Nelson H. C. Yung
Venue: Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision (2007)

In this paper, we present a new algorithm for estimating individual vehicle speed based on two consecutive images captured from a traffic safety camera system. Its principles are first, both images are transformed from the image plane to the 3D world coordinates based on the calibrated camera parameters. Second, the difference of the two transformed images is calculated, resulting in the background being eliminated and vehicles in the two images are mapped onto one image. Finally, a block feature of the vehicle closest to the ground is matched to estimate vehicle travel distance and speed. Experimental results show that the proposed method exhibits good and consistent performance. When compared with speed measurements obtained from speed radar, averaged estimation errors are 3.27% and 8.51% for day-time and night-time test examples respectively, which are better than other previously published results. The proposed algorithm can be easily extended to work on image sequences.