ppxscal/embedding_network huggingface dataset:
Scalable service oriented architecture for audio/video conferencing
Authors: Kishan G. Mehrotra, Geoffrey C. Fox
Venue:  (2005)

Audio/Video conferencing over Internet is increasing rapidly with the increase on the available network bandwidth and computing power. Even the cell phones will have the capacity to participate in videoconferencing sessions in the near future. This requires scalable and universally accessible videoconferencing systems. Increasingly diverse set of endpoints with various capabilities from cell phones to room based systems should be supported in such videoconferencing sessions. However, developing videoconferencing systems over Internet is a challenging task, since audio and video communications require high bandwidth and low latency. In addition, the processing of audio and video streams is computing intensive. Therefore, it is particularly difficult to develop scalable systems that support high number of users with various capabilities. Current videoconferencing systems can not fully address the problem of scalability and universal accessibility. Therefore, in this thesis we investigate scalable service oriented architecture for audio/video conferencing. We propose using a publish subscribe event broker network for the distribution of real-time audio/video streams in videoconferencing sessions and investigate the issues pertaining to scalability, performance, data representation and routing. We identify the requirements for the delivery of real-time audio/video traffic and incorporate necessary changes to the event delivery middleware. We present the results of extensive performance tests for the delivery of audio/video streams for both large and small size meetings in single and multiple broker settings. In addition, we propose a scalable and flexible architecture for meeting management and media processing, that can grow dynamically to provide services to higher number of users.
Phylogenetic Networks Based on the Molecular Clock Hypothesis
Authors: S. Bereg, Y. Zhang
Venue: Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering (2005)

A classical result in phylogenetic trees is that a binary phylogenetic tree adhering to the molecular clock hypothesis exists if and only if the matrix of distances between taxa is ultrametric. The ultrametric condition is very restrictive. In this paper we study phylogenetic networks that can be constructed assuming the molecular clock hypothesis. We characterize distance matrices that admit such networks for 3 and 4 taxa. We design an efficient algorithm for a special class of phylogenetic networks that can detect the existence of a network and constructs it.
A Shape Feature Based Image Retrieval in DCT Compressed-Domain
Authors: Zhang Xihuang, Bian Guochun, Xu Wenbo
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

In this paper, an approach of image retrieval directly based on shape feature in DCT compresseddomain is proposed. Firstly, according to the edge feature of DCT compressed image, the rough object shape is extracted from DCT compressed-domain to form a binary edge map; then the similarity measurement is redefined by using the moments invariant to improve the retrieval performance. It is supported by theoretical analysis and experimental result that this approach not only is fast, but also has a good performance. And it is also robust to rotation and translation.
Informed web content delivery
Authors: Leeann Bent
Venue:  (2005)

With the maturation of the World Wide Web, a variety of technologies have been created to optimize content delivery, such as caching, content delivery networks, and prefetching. While these techniques can be effective, it remains unclear how and when they are best used. This dissertation examines current Web performance practices and optimizations and provides a tool to improve Web performance by facilitating informed optimization of Web site content delivery to the end user. This dissertation first examines Web site performance from a user perspective by characterizing whole-page performance. While many performance optimizations are very effective on individual objects, they may not be effective across the whole page. Similarly, other optimizations may only be effective at the page level. Using our Medusa proxy, we find that the optimization that has the largest impact is parallel connections. Other performance optimizations only provide incremental benefit. In some cases this is due to limited opportunity for use, and, in these cases, clients would see better performance if these optimizations were more heavily used. This dissertation then examines Web site performance from a Web site perspective by analyzing the properties of a wide variety of web servers, focusing on content delivery. We find that our workload contains a much higher degree of uncacheable responses than previously found and that current practices impede Web site performance. We also performed a simulation analysis to estimate the potential performance benefits of content delivery networks (CDNs) for these Web sites. Our results indicate that Web sites benefit from the use of a CDN, but that CDNs can decrease the average request rate more than the peak request rate. Lastly, this dissertation presents the design and implementation of the Cassandra Toolkit, a tool that identifies performance problems and estimates the effect of performance optimizations on a Web site (e.g., a cache or CDN). We also validate the Cassandra Toolkit against a real optimization by comparing the Cassandra Toolkit's cache analysis with a real cache on actual Web site workloads. Finally, we show how the Cassandra Toolkit can optimize several real Web sites in different ways.
Clustering document images using a bag of symbols representation
Authors: Eugen Barbu, Pierre Heroux, Sebastien Adam, Eric Trupin
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

Document image classification is an important step in document image analysis. Based on classification results we can tackle other tasks such as indexation, understanding or navigation in document collections. Using a document representation and an unsupervised classification method, we may group documents that from the user point of view constitute valid clusters. The semantic gap between a domain independent document representation and the user implicit representation can lead to unsatisfactory results. In this paper we describe document images based on frequent occurring symbols. This document description is created in an unsupervised manner and can be related to the domain knowledge. Using data mining techniques applied to a graph based document representation we find frequent and maximal subgraphs. For each document image, we construct a bag containing the frequent subgraphs found in it. This bag of "symbols" represents the description of a document. We present results obtained on a corpus of 60 graphical document images.We present results obtained on a corpus of 60 graphical document images.
Comparisons of Multi-Resolution Analysis Methods for Mammogram and Fingerprint Image Compression
Authors: Dan V. Belc, Simon Y. Foo, Rodney G. Roberts
Venue: Proceedings of the 18th International Conference on Systems Engineering (2005)

This study presents a performance comparison analysis of Fourier Transform (FT), Discrete Cosine Transform (DCT), Wavelet Transform (WT), and Wavelet Packets (WP) on a 1024x1024, 12-bit mammogram and a 512x256, 8-bit, fingerprint image. In the multi-resolution analysis methods, three to five level decompositions and different entropy models at any decomposition levels will be used. An adaptable signal decomposition algorithm for minimizing the decomposition tree will also be introduced. The images are first segmented into two regions: region of interest (ex. micro-calcification in the mammograms), and the background region. The two regions are then compressed at two different levels, to better preserve the information in the image, but most importantly in the region of interest. The quality of the resultant compressed images is subjected to visual analysis by a group of 30 non-experts students, as well as analyzed objectively based on the peak signal-to-noise ratio (PSNR), mean square error (MSE), and reconstruction error. This study could potentially help radiologists and fingerprint experts better detect the important details in the images. Furthermore, the results will save storage space, reduce access time, and improve the accuracy of diagnosis - in other words, cost savings. The compressed images are also better suited for remote access and transfer, for tele-diagnostic, and tele-medicine research and training.
Managing of Cooperative Genetic Algorithms by Intelligent Agent
Authors: Halina Kwasnicka, Magdalena Gierusz
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

Genetic Algorithms (GAs) are very popular optimization tool, although efficient applications of GAs requires users have problem with setting their parameters and used genetic operators to obtain satisfactory solution in acceptable time. We propose an intelligent agent as a control mechanism for a group of cooperating genetic algorithms. A core of the system is a family of cooperating genetic algorithms. Manager, a kind of Fuzzy Expert System, is responsible for control of GAs to assure effectiveness of the search process. It requires providin knowledge concerning influence of some parameters of GAs on tempo and mode of evolution. Such knowledge in the form of fuzzy inference rules should be included into Manager. Analyser - the third part of the system, will gather knowledge concerning progress and actual state of a working system. This knowledge will be used in the form of facts to fire suitable rules. The simulation study of efficiency of developed system is presented and discussed.
A Study on Textual Entailment
Authors: Vasile Rus, Art Graesser, Philip M. McCarthy, King-Ip Lin
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

In this paper we study a graph-based approach to the task of textual entailment between a Text and Hypothesis. The approach takes into account the full lexico-syntactic context of both the Text and Hypothesis and relies heavily on the concept of subsumption. It starts with mapping the Text and Hypothesis into graph structures where nodes represent concepts and edges represent lexico-syntactic relations among concepts. Based on a subsumption score between the Text-graph and Hypothesis-graph an entailment decision is then made. The impact of synonymy on entailment is quantified and discussed. An important advantage of our solution is the ability to customize it so that high-confidence results are obtained.
Evaluating machine learning for information extraction
Authors: Neil Ireson, Fabio Ciravegna, Mary Elaine Califf, Dayne Freitag, Nicholas Kushmerick, Alberto Lavelli
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

Comparative evaluation of Machine Learning (ML) systems used for Information Extraction (IE) has suffered from various inconsistencies in experimental procedures. This paper reports on the results of the Pascal Challenge on Evaluating Machine Learning for Information Extraction, which provides a standardised corpus, set of tasks, and evaluation methodology. The challenge is described and the systems submitted by the ten participants are briefly introduced and their performance is analysed.
A Computer Vision System on a Chip: a case study from the automotive domain
Authors: Gideon P. Stein, Elchanan Rushinek, Gaby Hayun, Amnon Shashua
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

The automotive market puts strict and often conflicting requirements on computer vision systems. On the one hand the algorithms require considerable computing power to work reliably in real-time and under a wide range of lighting conditions. On the other hand, the cost must be kept low, the package size must be small and the power consumption must be low. In addition, automotive qualified parts must be used both to withstand the harsh operating environment and to guarantee long product life. To meet all these conflicting requirements Mobileye developed the EyeQ, a complete ¿system on a chip¿ (SoC) which has the computing power to support a variety of applications such as lane, vehicle and pedestrian detection. This paper describes the process of designing an ASIC to support a family of vision algorithms.
Sensor network software update management: a survey
Authors: Chih-Chieh Han Ram Kumar Roy Shea Mani Srivastava
Venue: International Journal of Network Management (2005)

Software management is a critical task in the system administration of enterprise-scale networks. Enterprise-scale networks that have traditionally comprised of large clusters of workstations are expanding to include low-power ad hoc wireless sensor networks (WSN). The existing tools for software updates in workstations cannot be used with the severely resource-constrained sensor nodes. In this article, we survey the software update techniques in WSNs. We base our discussion around a conceptual model for the software update tools in WSNs. Three components of this model that we study are the execution environment at the sensor nodes, the software distribution protocol in the network and optimization of transmitted updates. We present the design space of each component and discuss in-depth the trade-offs that need to be considered in making a particular design choice. The discussion is interspersed with references to deployed systems that highlight the design choices.
Moving Target Indication and Tracking from Moving Sensors
Authors: Ronald Jones, Branko Ristic, Nicholas J. Redding, David M. Booth
Venue: Proceedings of the Digital Image Computing on Techniques and Applications (2005)

This paper describes a moving target indication and tracking system developed for acquiring and tracking targets in video from moving sensors, in particular airborne urban surveillance video. The paradigm of the moving sensor, which is a typical scenario in defence applications (e.g. UAV surveillance video), poses some unique problems as compared to the stationary sensor. Our solution draws on a number of algorithms from the vision and tracking communities and combines them as a novel solution to the problem. Moreover, given a suitable cluster of conventional hardware, the system allows a near real-time solution to MTI.
A job-centric approach to user-level intrusion detection
Authors: Shambhu Upadhyaya
Venue:  (2005)

Intrusion detection attempts to detect attacker activity should the preventive measures be inadequate. User-level intrusion detection attempts to deter and curtail an attack even after the system has been compromised. In this dissertation, the problem of user-level intrusion detection is approached in a more holistic manner. Currently known user-level intrusion detection algorithms rely on establishing statistically that an observed stream of commands belongs to a person other than the profiled user. However, by viewing the command stream merely as text, several useful properties about how a user uses a computer system are lost or incorrectly represented. The first part of the dissertation deals with this shortcoming. A novel higher order representation of a user's profile is proposed, which includes the hierarchical notion of jobs/tasks, followed by the basic units of functionality which a user requires to accomplish these tasks and then the actual commands. Such a representation is a significant departure from known techniques and provides several benefits such as user involvement in the security process, lowered false positive rates and per job profiling. Depending on which site the security system is deployed and what level at that site, a range of IDS components may be exposed to direct attack. Indeed, if the IDS is very effective, then the IDS itself becomes a more lucrative target. This is particularly of concern to a user-level IDS which is implemented in close vicinity to the user. In this dissertation, this specific issue is also addressed, wherein a structural analysis of dependencies reveals the ideal tamper-resistant configuration. Finally, investment in security systems of any kind and where they are planned to be installed requires careful deliberation. The fact that various options cannot be tried and tested on a live network, leaves the security analyst with very little leeway. Threat models provide a very useful and viable alternative in this regard. However, for user-level threats, currently known techniques such as attack graphs and privilege graphs are not appropriate. Instead, a new model is proposed called the key challenge graph, which specifically looks at user-level threat modeling. (Abstract shortened by UMI.)
Experiences using SPARK in an undergraduate CS course
Authors: Anthony S. Ruocco
Venue: ACM SIGAda Ada Letters (2005)

This paper describes experiences garnered while teaching a course on high integrity software using SPARK to a mix of junior and senior level undergraduates. The paper describes the impact of pre-requisites, course layout and execution, and lessons learned by students and the instructor. The course used the SPARK toolset provide by Praxis High Integrity Systems, and the Gnat Programming System (GPS) provided by AdaCore Technologies (ACT) under the Ada Academic Initiative Program. Details about using these tools is integrated through out the paper.
Adaptive Probabilistic Tracking Embedded in a Smart Camera
Authors: Sven Fleck, Wolfgang Strasser
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

Tracking applications based on distributed and embedded sensor networks are emerging today, both in the field of surveillance (airports, lab facilities, train stations, museums, public spots) and industrial vision (visual servoing, factory automation). Traditional centralized approaches offer several drawbacks, due to limited communication bandwidth, computational requirements and thus also limited spatial camera resolution and framerate. In this paper, we present a network-enabled Smart Camera for probabilistic tracking. It is capable of tracking objects adaptively in real-time and offers a very bandwidthconservative approach, as the whole computation is performed embedded in the Smart Camera, and only the tracking results are transmitted which are on a higher level of abstraction.
Dynamic voltage and frequency scaling under a precise energy model considering variable and fixed components of the system power dissipation
Authors: Kihwan Choi, Wonbok Lee, R. Soma, M. Pedram
Venue: Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design (2004)

This work presents a dynamic voltage and frequency scaling (DVFS) technique that minimizes the total system energy consumption for performing a task while satisfying a given execution time constraint. We first show that in order to guarantee minimum energy for task execution by using DVFS it is essential to divide the system power into active and standby power components. Next, we present a new DVFS technique, which considers not only the active power, but also the standby component of the system power. This is in sharp contrast with previous DVFS techniques, which only consider the active power component. We have implemented the proposed DVFS technique on the BitsyX platform - an Intel PXA255-based platform manufactured by ADS Inc., and report detailed power measurements on this platform. These measurements show that, compared to conventional DVFS techniques, an additional system energy saving of up to 18% can be achieved while satisfying the user-specified timing constraints.
Distributed Policy Specification and Enforcement in Service-Oriented Business Systems
Authors: W. T. Tsai, Xinxin Liu, Yinong Chen
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

Service-Oriented Computing (SOC) and Web Services (WS) provide a flexible computing platform for electronic business and commerce. Introducing policy-based computing to service-oriented business systems adds another dimension of flexibility and security. While service composition and re-composition in service-oriented business systems allow major system reconstruction, policy-based computing can better deal with the small and routine changes of business processing. This paper reports our latest research on integrating policy-based computing into service-oriented business system and discusses its feasibility, benefits and cost. Under this research, we designed a policy specification and enforcement language PSEL for specifying system constraints and business rules. We implemented a runtime environment in which a service-oriented business system can be modeled, analyzed, deployed, and executed with policy enforcement. Automated tools have been developed to facilitate the entire development process. The cost of policy-based computing is experimentally evaluated.
Dead live longer: a dramoletto
Authors: Christoph Grein
Venue: ACM SIGAda Ada Letters (2005)

A large and dark room. In the foreground a terminal, at the rear wall a huge screen showing everything that happens at the terminal. At first the screen is off, the room in twilight. Below the stage, but visible, Lady Ada in a coffin. Around the stage on a gallery, nearly invisible in the dark (also when the stage is lit), the chorus of Ada gurus.
The 8 requirements of real-time stream processing
Authors: Michael Stonebraker, Uǧur Çetintemel, Stan Zdonik
Venue: ACM SIGMOD Record (2005)

Applications that require real-time processing of high-volume data steams are pushing the limits of traditional data processing infrastructures. These stream-based applications include market feed processing and electronic trading on Wall Street, network and infrastructure monitoring, fraud detection, and command and control in military environments. Furthermore, as the "sea change" caused by cheap micro-sensor technology takes hold, we expect to see everything of material significance on the planet get "sensor-tagged" and report its state or location in real time. This sensorization of the real world will lead to a "green field" of novel monitoring and control applications with high-volume and low-latency processing requirements.Recently, several technologies have emerged---including off-the-shelf stream processing engines---specifically to address the challenges of processing high-volume, real-time data without requiring the use of custom code. At the same time, some existing software technologies, such as main memory DBMSs and rule engines, are also being "repurposed" by marketing departments to address these applications.In this paper, we outline eight requirements that a system software should meet to excel at a variety of real-time stream processing applications. Our goal is to provide high-level guidance to information technologists so that they will know what to look for when evaluation alternative stream processing solutions. As such, this paper serves a purpose comparable to the requirements papers in relational DBMSs and on-line analytical processing. We also briefly review alternative system software technologies in the context of our requirements.The paper attempts to be vendor neutral, so no specific commercial products are mentioned.