ppxscal/embedding_network huggingface dataset:
Elastic Hierarchies: Combining Treemaps and Node-Link Diagrams
Authors: Shengdong Zhao, Michael J. McGuffin, Mark H. Chignell
Venue: Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization (2005)

We investigate the use of elastic hierarchies for representing trees, where a single graphical depiction uses a hybrid mixture, or "interleaving", of more basic forms at different nodes of the tree. In particular, we explore combinations of node-link and Treemap forms, to combine the space-efficiency of Treemaps with the structural clarity of node-link diagrams. A taxonomy is developed to characterize the design space of such hybrid combinations. A software prototype is described, which we used to explore various techniques for visualizing, browsing and interacting with elastic hierarchies, such as side-by-side overview and detail views, highlighting and rubber banding across views, visualization of multiple foci, and smooth animations across transitions. The paper concludes with a discussion of the characteristics of elastic hierarchies and suggestions for research on their properties and uses.
EasiPC: A Packet Compression Mechanism for Embedded WSN
Authors: Hailing Ju, Li Cui
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

Wireless sensor network (WSN) has many promising applications. One of the most challenging technical issues for sensor network design is to enable ultra low power consumption communication. In this paper we propose a packet compression mechanism, namely EasiPC, as a new power management technique for WSN. With this mechanism, the lengths of data packets are shortened significantly due to the effective reduction of redundant information. As a consequence the energy required for transporting packets is saved too. Experiments carried out on WSN platform developed in-house show that this packet compression mechanism is both feasible and effective. Additional benefits introduced by this packet compression mechanism include reduced transmission delays, reduced channel accessing collisions, as well as enhanced channel utilization.
Panel Summaries
Venue: IEEE Design Test (2005)

An evening panel session entitled "Microelectronics and Test in 'The New Europe'--Challenges and Opportunities in Research and Industry," took place on 23 May at the 10th European Test Symposium (ETS 05). Raimund Ubar and Hans-Joachim Wunderlich (University of Stuttgart) organized the panel session, and Erik Jan Marinissen (Philips Research) served as moderator. Panelists included representatives of the Eastern European countries that have recently joined the EU, those who live and work outside the EU, and Western companies with branches or subcontractors in Eastern European countries.A panel session at the 3rd IEEE Infrastructure IP (IIP) Workshop held in conjunction with the VLSI Test Symposium focused on the question,"Is silicon debug the Cinderella of infrastructure IP?" IEEE Design & Test coorganized the panel session, and R. Chandramouli of Virage Logic served as chair.
Phishing Webpage Detection
Authors: Liu Wenyin, Guanglin Huang, Liu Xiaoyue, Xiaotie Deng, Zhang Min
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

An approach to detection of phishing webpages based on visual similarity is proposed, which can be utilized as a part of an enterprise solution to anti-phishing. A legitimate webpage owner can use this approach to search the Web for suspicious webpages which are visually similar to the true webpage. The approach first decomposes the webpages into salient (visually distinguishable) block regions. The visual similarity between two webpages is then evaluated in three metrics: block level similarity, layout similarity, and overall style similarity. A webpage is reported as a phishing suspect if any of them (with regards to the true one) is higher than its corresponding preset threshold. Preliminary experiments show that the approach can successfully detect those phishing webpages with few false alarms at a speed adequate for online application.
A resource manager for optimal resource selection and fault tolerance service in Grids
Authors: P. Z. Kolano
Venue: Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid (2004)

In this paper, we address the issues of resource management and fault tolerance in Grids. In Grids, the state of the selected resources for job execution is a primary factor that determines the computing performance. Specifically, we propose a resource manager for optimal resource selection. The resource manager automatically selects the optimal resources among candidate resources using a genetic algorithm. Typically, the probability of failure is higher in Grid computing than in a traditional parallel computing and the failure of resources affects job execution fatally. Therefore, a fault tolerance service is essential in computational Grids and Grid services are often expected to meet some minimum levels of quality of service (QoS) for desirable operation. To address this issue, we also propose fault tolerance service to satisfy QoS requirements. We extend the definition of failures, such as process failure, processor failure, and network failure, and design the fault detector and fault manager. The simulation results indicate that our approaches are promising in that (1) our resource manager finds the optimal set of resources that guarantees the optimal performance; (2) the fault detector detects the occurrence of resource failures; and (3) the fault manager guarantees that the submitted jobs complete and improves the performance of job execution due to job migration even if some failures happen.
Effectiveness of Artificial Neural Networks Adaptation According to Time Period of Training Data Acquisition
Authors: Adrian Horzyk, Ewa Dudek-Dyduch
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

Artificial Neural Networks (ANNs) were inspired by Natural Neural Networks (NNNs) and natural processes of training. The NNNs receive data in time still tuning the inner model of the surrounding world. These valuable features of our brains let us to dynamically accommodate themselves to the changes surround. These features make us possible to forget some irrelevant information, correct our knowledge and meet truth. ANNs usually work on the training data (TD) acquired in the past and totally known at the beginning of the adaptation process. Because of this the adaptation methods of the ANNs can be sometimes more effective than the natural training process observed in the NNNs. This paper discusses the ability of ANNs to adapt more effectively than NNNs do if only the TD are completely given at the beginning of the adaptation process. In this case the adaptation process of ANNs can be divided into two steps: analyze or examining the set of TD and construction of neural network topology and weights computation. Two different applications areas of such approach are presented in the paper.
Proof of Monotone Loss Rate of Fluid Priority-Queue with Finite Buffer
Authors: Stephen L. Spitler, Daniel C. Lee
Venue: Queueing Systems: Theory and Applications (2005)

This paper studies a fluid queueing system that has a single server, a single finite buffer, and which applies a strict priority discipline to multiple arriving streams of different classes. The arriving streams are modeled by statistically independent, identically distributed random processes. A proof is presented for the highly intuitive result that, in such a queueing system, a higher priority class stream has a lower average fluid loss rate than a lower priority class stream. The proof exploits the fact that for a work-conserving queue, the fluid loss rate for a given class is invariant of what queueing discipline is applied to all arriving fluid of this particular class.
The documentation delivery problem
Authors: T. D. C. Kuch
Venue: ACM SIGDOC Asterisk Journal of Computer Documentation (1976)

Suppose you have written the perfect documentation package for a system. Further, suppose you update the documentation instantaneously every time the system changes (Suppose we conquer cancer; suppose we travel faster than light). But, even if this impossible goal is realized, what then? 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
Evaluating and Improving Integration Quality for Heterogeneous Data Sources Using Statistical Analysis
Authors: Evgeniya Altareva, Stefan Conrad
Venue: Proceedings of the 9th International Database Engineering & Application Symposium (2005)

This paper considers the problem of integrating heterogeneous semi-structured data sources with the purpose of estimating integration quality (IQ). Integration of such data sources leads to results with unpredictable trustworthiness and none of the existing methods is capable of accounting for the uncertainty which is accumulated over all of the integration steps and which affects integration quality. To compute the uncertainties we suggest using a well-establishedstatistical method Latent Class Analysis (LCA). This method allows to analyze the influence of the latent factors associated with the real-world entities on the set of data. We show on examples how the proposed approach can be used for evaluating and improving IQ giving an important tool to the users concerned with the data¿s trustworthiness.
Adaptive Spam Filtering Using Dynamic Feature Space
Authors: Yan Zhou, Madhuri S. Mulekar, Praveen Nerellapalli
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Unsolicited bulk e-mail, also known as spam, has been an increasing problem for the e-mail society. This paper presents a new spam filtering strategy that 1) uses a practical entropy coding technique, Huffman coding, to dynamically encode the feature space of e-mail collections over time and, 2) applies an online algorithm to adaptively enhance the learned spam concept as new e-mail data becomes available. The contributions of this work include a highly efficient spam filtering algorithm in which the input space is radically reduced to a single-dimension input vector, and an adaptive learning technique that is robust to vocabulary change, concept drifting and skewed data distribution. We compare our technique to several existing off-line learning techniques including Support Vector Machine, Na¨ýve Bayes, -Nearest Neighbor, C4.5 decision tree, RBFNetwork, Boosted decision tree and Stacking, and demonstrate the effectiveness of our technique by presenting the experimental results on the e-mail data that is publicly available.
A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment
Authors: A. M. Manning, D. J. Haglin
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

We present SUDA2, a recursive algorithm for finding Minimal Sample Uniques (MSUs). SUDA2 uses a novel method for representing the search space forMSUs and new observations about the properties ofMSUs to prune and traverse this space. Experimental comparisons with previous work demonstrate that SUDA2 is not only several orders of magnitude faster but is also capable of identifying the boundaries of the search space, enabling datasets of larger numbers of columns than before to be addressed.
A Task Decomposition Algorithm Using Radial Basis Functions for Classification Problems
Authors: Seiji Ishihara, Harukazu Igarashi
Venue: Proceedings of the Digital Image Computing on Techniques and Applications (2005)

This paper proposes an algorithm for decomposing a multi-class classification problem into a set of two-class classification problems. The algorithm divides a set of input pattern vectors in each class into subsets according to the distribution of the selected input pattern vectors. The distribution is represented by RBF network, whose parameters are estimated according to the evaluation based on MDL criterion. In this paper, the algorithm applied for constructing a modular neural network. Experimental results showed that the algorithm simplifies multi-class classification problems effectively.
An Automatic Code Generation Tool for Partitioned Software in Distributed Systems
Authors: Viswanath Sairaman, Nagarajan Ranganathan, Neeta S. Singh
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

In distributed heterogeneous systems, the target application is partitioned and the partitions are executed in different computing units while satisfying the dependencies between the code partitions. Code generation is the process of converting the code partitions into individually executable code clusters and satisfying the code dependencies by adding communication primitives to send and receive data between dependent the code clusters. In this work, we describe a code generation tool that is applicable to procedural language based applications for distributed processing. The application programs along with the partition primitives are converted into independently executable concrete implementations. The process consists of two steps, first translating the primitives of the application program into equivalent code clusters, and then scheduling the implementations of these code clusters according to the inherent data dependencies. Further, the original source code needs to be reverse engineered in order to create a meta-data table describing the program elements and dependency trees. This data gathered, is used along with Parallel Virtual Machine (PVM) primitives for enabling the communication between the partitioned programs in the distributed environment. The proposed code generation model has been implemented using C and tested for various application programs for functional verification.
Benchmarking the Dependability of Windows and Linux Using PostMark™ Workloads
Authors: Karama Kanoun, Yves Crouzet, Ali Kalakech, Ana-Elena Rugina, Philippe Rumeau
Venue: Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (2005)

This paper presents a dependability benchmark for general-purpose operating systems and its application to six versions of Windows operating system and four versions of Linux operating system. The benchmark measures are: operating system robustness (as regards possible erroneous inputs provided by the application software to the operating system via the application programming interface), reaction and restart times in the presence of faults. The workload is PostMark, a file system performance benchmark for operating systems.
Automatically Generating User Interfaces for Device Federations
Authors: Elmar Braun, Max Muhlhauser
Venue: Proceedings of the Seventh IEEE International Symposium on Multimedia (2005)

One of the ideas of ubiquitous computing is that computing resources should be embedded ubiquitously in the environment, making them available to any nearby users. Some researchers have applied this to interaction, and tried to embed an abundance of interactive devices, such as touch screens, in rooms and whole buildings. The opposite concept is that of a single personal mobile device, which users carry at all times and use for all interactions. Because both concepts have different strengths, we explore building interfaces for federations of personal mobile and stationary embedded devices, exploiting the capabilities of both rather than forcing users to choose between either. We have developed an infrastructure that coordinates multiple devices for that purpose: groups of devices work together to render a user interface. As one of the main challenges for such federated user interfaces we have identified their authoring. How should the interface be divided in multiple parts, and can that decision be made by a computer rather than a human designer?
Simultaneous escape routing and layer assignment for dense PCBs
Authors: M. M. Ozdal, M. D. F. Wong
Venue: Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design (2004)

As die sizes are shrinking, and circuit complexities are increasing, the PCB routing problem becomes more and more challenging. Traditional routing algorithms can not handle these challenges effectively, and many high-end designs in the industry require manual routing efforts. In this paper, we propose a problem decomposition that distinguishes routing within dense components from routing in the intermediate area. In particular, we propose an effective methodology to find the escape routing solution for multiple components simultaneously such that the number of crossings in the intermediate area is minimized. For this, we model the problem as a longest path with forbidden pairs (LPFP) problem, and propose two algorithms for it. The first is an exact polynomial-time algorithm that is guaranteed to find the maximal planar routing solution on one layer. The second is a randomized algorithm that has good scalability characteristics for large circuits. Then we use these algorithms to assign the maximal subset of planar nets to each layer, and then distribute the remaining nets at the end. We demonstrate the effectiveness of these algorithms through experiments on industrial circuits.
Verify Results of Network Intrusion Alerts Using Lightweight Protocol Analysis
Authors: Jingmin Zhou, Adam J. Carlson, Matt Bishop
Venue: Proceedings of the 21st Annual Computer Security Applications Conference (2005)

We propose a method to verify the result of attacks detected by signature-based network intrusion detection systems using lightweight protocol analysis. The observation is that network protocols often have short meaningful status codes saved at the beginning of server responses upon client requests. A successful intrusion that alters the behavior of a network application server often results in an unexpected server response, which does not contain the valid protocol status code. This can be used to verify the result of the intrusion attempt. We then extend this method to verify the result of attacks that still generate valid protocol status code in the server responses. We evaluate this approach by augmenting Snort signatures and testing on real-world data. We show that some simple changes to Snort signatures can effectively verify the result of attacks against the application servers, thus significantly improve the quality of alerts.
Parallel and Distributed Computing for Cybersecurity
Authors: Vipin Kumar
Venue: IEEE Distributed Systems Online (2005)

Parallel and distributed data mining offer great promise for addressing cybersecurity. The Minnesota Intrusion Detection System can detect sophisticated cyberattacks on large-scale networks that are hard to detect using signature-based systems.
Alternate optimal solutions
Authors: C. A. Haverly
Venue: Issue 28 (January 1980) (1980)

The behavior of LP models is a topic in which I have had some interest in recent years. I speak of behavior of the model itself, as distinct from the behavior of the algorithm, the solution path or the accuracy of the model representation. I have submitted several papers on this topic before to the SIGMAP bulletin (1, 2, 3). In this paper I consider model behavior as reflected in alternate optimal solutions.
CAD Tools for a Globally Asynchronous Locally Synchronous FPGA Architecture
Authors: Xin Jia, Ranga Vemuri
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

The performance of FPGAs is suffering from interconnect delays, especially the delays of the long wires which can be more than 10ns in large FPGAs. We have proposed the GAPLA: a Globally Asynchronous Locally Synchronous (GALS) FPGA architecture to deal with this problem. In GAPLA architecture, the whole FPGA area is divided into locally synchronous blocks wrapped with asynchronous I/O interfaces. Interconnections inside each synchronous block are local and fast. The long interconnections between synchronous blocks only come into picture when there are asynchronous communications. In this paper, we focus on the CAD tools designed for the GAPLA architecture. Starting from a behavioral circuit description, a design is first partitioned into smaller modules where each module can fit into one synchronous block. Then an As-Soon-As-Possible scheduler (other scheduler can also be applied) is used to schedule each module. After scheduling, control signals of the asynchronous communications are added to each module since the communication timing is now known in the scheduled design. Each module is then synthesized and mapped into a synchronous block using existing CAD tools for synchronous FPGAs. A module mapping process is used to find the implementation location for each module. Experimental results show that applications could run upto 2 times faster on the GAPLA FPGA compared to the synchronous FPGA counterparts.
Subgoal Ordering and Granularity Control for Incremental Planning
Authors: Chih-Wei Hsu, Yixin Chen
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

In this paper, we study strategies in incremental planning for ordering and grouping subproblems partitioned by the subgoals of a planning problem when each sub-problem is solved by a basic planner. To generate a rich set of partial orders for ordering subproblems, we propose a new ordering algorithm based on a relaxed plan built from the initial state to the goal state. The new algorithm considers both the initial and the goal states and can effectively order subgoals in such a way that greatly reduces the number of invalidations during incremental planning. We have also considered trade-offs between the granularity of the subgoal sets and the complexity of solving the overall planning problem. We show an optimal region of grain size that minimizes the total complexity of incremental planning. We propose an efficientstrategy to dynamically adjust the grain size in partitioning in order to operate in this optimal region. We further evaluate a redundant-execution scheme that uses two different subgoal orders in order to improve the quality of the plans generated without greatly sacrificing run-time efficiency. Experimental results on using three basic planners (Metric-FF, YAHSP, and LPG-TD-speed) show that our strategies are general for improving the time and quality of each of these planners across various benchmarks.
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
Authors: Franz Pernkopf, Jeff Bilmes
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either maximum likelihood (ML) or conditional maximum likelihood (CL) to optimize network parameters. For structure learning, we use either conditional mutual information (CMI), the explaining away residual (EAR), or the classification rate (CR) as objective functions. Experiments with the naive Bayes classifier (NB), the tree augmented naive Bayes classifier (TAN), and the Bayesian multinet have been performed on 25 data sets from the UCI repository (Merz et al., 1997) and from (Kohavi & John, 1997). Our empirical study suggests that discriminative structures learnt using CR produces the most accurate classifiers on almost half the data sets. This approach is feasible, however, only for rather small problems since it is computationally expensive. Discriminative parameter learning produces on average a better classifier than ML parameter learning.