ppxscal/embedding_network huggingface dataset:
Genetic Simulated Annealing Algorithm for Optimal Deployment of Flow Monitors
Authors: Jin Zhang, Xiaohui Zhang, Jiangxin Wu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

In order to monitor a large fraction of IP flows in an IP network concurrently, a set of flow monitors are needed to be deployed at multiple locations within the network. The problem of Optimal Deployment of Flow Monitors (ODFM) concerns that where to place monitors and how to control their sampling rate so that the maximum monitoring reward can be got under certain monitoring cost constraint. After modeling the monitoring reward and the monitoring cost appropriately, we formulate ODFM as a non-linear programming problem, and propose a Genetic Simulated Annealing (GSA) algorithm which combines the Standard Genetic (SG) algorithm and the simulated annealing algorithm to solve it. We evaluate the performance of the GSA and compare it to that of the SG through experiments on synthetic network topologies. The experimental results show that the GSA outperforms the SG by up to 15% in terms of quality of solutions.
IGES: A Key to CAD/CAM Systems Integration
Authors: Bradford Smith
Venue: IEEE Computer Graphics and Applications (1983)

The data exchange specification is now well developed and tested, and more than 30 graphics system vendors have promised to supply IGES translators for their products.
The anatomy of Clickbot.A
Authors: Neil Daswani, Michael Stoppelman
Venue: Proceedings of the first conference on First Workshop on Hot Topics in Understanding Botnets (2007)

This paper provides a detailed case study of the architecture of the Clickbot. A botnet that attempted a low-noise click fraud attack against syndicated search engines. The botnet of over 100,000 machines was controlled using a HTTP-based botmaster. Google identified all clicks on its ads exhibiting Clickbot. Alike patterns and marked them as invalid. We disclose the results of our investigation of this botnet to educate the security research community and provide information regarding the novelties of the attack.
A Topology Control Scheme for Avoiding Sensing Hole in Wireless Sensor Networks
Authors: Kyungjun Kim, Byungrae Cha
Venue: Proceedings of the The 2007 International Conference Computational Science and its Applications (2007)

One of the main challenges in wireless sensor networks is to maximize network life time and to minimize power consumption. We propose an energy efficient mechanism for selecting active node which involved in sensing operation in a given dense field. This mechanism can reduce the communication cost by decreasing the number of sensing nodes in highly dense area. Our simulation results show that our mechanism reduces the number of transmitted packets the maximum 60% in dense sensing area.
Crypto-fraglets: networking, biology and security
Authors: Marinella Petrocchi
Venue: Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems (2006)

The paper describes connections between two models dealing with communication protocols, the fraglet model and the formal language of MultiSet Rewriting, which has very good inspiration from biology. By starting from similarities in their capabilities of modeling (indeed, their strong analogies in modeling biological systems), the programming language of the first model is translated into rule of the second model. Moreover, we propose an extended version of fraglets, namely Crypto-fraglets, as an initial step towards the intent of enlarging the set of communication protocols that this framework is currently able to describe, model and simulate.
Bridging the Semantic Gap: Visualizing Transition Graphs with User-Defined Diagrams
Authors: A. Johannes Pretorius, Jarke J. van Wijk
Venue: IEEE Computer Graphics and Applications (2007)

Users are often faced with large data sets in which the underlying meaning of the data is clear, but sense-making is difficult. State transition graphs fit this description well. Users associate precise semantics with multivariate attributes that describe nodes, but current visualization techniques do not exploit this. Consequently, users have to invest significant effort to interpret and understand visualizations. We present a novel technique that bridges this semantic gap by enabling the user to define custom diagrams that closely reflect the associated semantics. User-defined diagrams are incorporated in a number of correlated visualizations that support different user needs. To show the merit of our approach, the authors discuss two real-world applications.
Envisioning the Wind: Meteorology Graphics at Weather Underground
Authors: Tom Geller
Venue: IEEE Computer Graphics and Applications (2007)

Weather Underground has delivered real-time weather data to the public for free since it was created in 1991 at the University of Michigan. Today, more than 11 million people visit the company's Web site per month. This article discusses advances in meteorology graphics and the keys to Weather Underground's successes.
Robust Classification of Dialog Acts from the Transcription of Utterances
Authors: Mohammad S. Sorower, Mohammed Yeasin
Venue: Proceedings of the International Conference on Semantic Computing (2007)

This paper presents a robust classification of dialog acts from text utterances. Two different types, namely, bag-of-words and syntactic relationship among words, were used to extract the discourse level features from the transcript of utterances. Subsequently a number of feature mining methods have been used to identify the most relevant features and their roles in classifying dialog acts. The selected features are used to learn the underlying models of dialog acts using a number of existing machine learning algorithms from the WEKA toolbox. Empirical analyses using the HCRC Map Task Corpus dialog data was conducted to evaluate the performance of the proposed approach.
Program Behavior at the Symbolic Level
Authors: A. Batson
Venue: Computer (1976)

No application programmer writes machine-language programs-i.e., strings of ones and zeroes. That primitive pursuit has long been reserved for those few who create the very first modules of a software system for new hardware. Instead, programmers make use of a wide spectrum of symbolic programming languages, ranging from assembly code to high-level languages such as Fortran, Cobol, and the Algol family. Every programming language has semantics which define some abstract machine. For the assembly-language programmer this machine bears a great resemblance to the actual hardware on which the program will be interpreted, but even here the programmer will frequently use system-defined subroutines or macros which represent extensions of the base hardware facilities. The high-level language programmer's abstract machine reflects the control mechanisms and data structures characteristic of the language. The Fortran programmer, for example, can think in terms of multidimensional array structures, DO loops, subprogram facilities, and so on. In principle he need never be concerned with the manner in which his abstract Fortran machine is to be realized by a particular hardware and software system. The user of a modern electronic hand calculator needs no knowledge of the works inside the box, and a modern high-level language system should present to its users an equally consistent environment, completely defined in terms of the syntax and semantics of the source language.
Forecast approach using neural network adaptation to support vector regression grey model and generalized auto-regressive conditional heteroscedasticity
Authors: Bao Rong Chang, Hsiu Fen Tsai
Venue: Expert Systems with Applications: An International Journal (2008)

In order to reduce the volatility clustering effect that deteriorate the efficiency and effectiveness of time series prediction and gives rise to large residual errors, a composite method, which is SVRGM/GARCH model with neural network adaptation, is introduced to improve the predictive accuracy of the complex time series, e.g. stocks price index or futures trading index. A support vector regression (SVR) is employed to improve the control and environment parameters of grey model (GM) denoted by SVRGM. Thus, SVR learning functions to highly reduce the overshoot effect when GM is applied to time series prediction. Moreover, a generalized auto-regressive conditional heteroscedasticity (GARCH) is utilized to resolve the problem of volatility clustering in time series so as to best fit the model. Incorporating GARCH model into SVRGM prediction is scheming to effectively and efficiently tackle two crucial problems, the overshoot and volatility clustering effects, simultaneously. This composite system is adapted optimally by back-propagation neural network (BPNN).
Effect of static analysis tools on software security: preliminary investigation
Authors: Vadim Okun, William F. Guthrie, Romain Gaucher, Paul E. Black
Venue: Proceedings of the 2007 ACM workshop on Quality of protection (2007)

Static analysis tools can handle large-scale software and find thousands of defects. But do they improve software security? We evaluate the effect of static analysis tool use on software security in open source projects. We measure security by vulnerability reports in the National Vulnerability Database.
Allocation heuristics and defragmentation measures for reconfigurable systems management
Authors: Jesús Tabero, Julio Septién, Hortensia Mecha, Daniel Mozos
Venue: Integration, the VLSI Journal (2008)

A novel technique is proposed for the management of a 2D reconfigurable device in order to get true hardware multitasking. We use a Vertex List Set to keep track of the free area boundary. This structure contains the best candidate locations for the task, and several heuristics are proposed to select one of them, based in fragmentation and adjacency. A Look-Ahead heuristic that anticipates the next known event is also proposed. A metric is used to estimate the fragmentation status of the FPGA, based on the number of holes and their shape. Defragmentation measures are taken when needed.
A Very Fast Parallel Processor
Authors: N. H. Christ
Venue: IEEE Transactions on Computers (1984)

A parallel processor specially designed for an important problem in theoretical physics is described. The final device will contain 256 nodes running in lock-step in a SIMD mode with a computational power of 4 billion 22-bit floating point operations per second. Each node is controlled by an Intel 80286/287 microprocessor, contains 160K bits of memory and has a pipelined, microprogrammable arithmetic unit which performs floating point multiplications and additions. The nodes are interconnected in a two-dimensional rectangular grid so that vectorized arithmetic can be performed using data stored on any two adjacent nodes.
Overview of LDPC Codes
Authors: Zongjie Tu, Shiyong Zhang
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

In light of the history of LDPC codes and relevant research advances in recent years, this paper probes into the encoding and decoding techniques related to this capacity-approaching error-correction technology. Besides the general expression as an equation, LDPC codes can also be examined with a Tanner graph. The encoding of LDPC codes comprises two tasks: construct a sparse parity-check matrix, and generate codewords with the matrix. The decoding of LDPC codes can be divided into three phases: initialization, message update, and validation. With a conventional model of communication systems, common decoding algorithms of LDPC codes are scrutinized. In particular, the sum-product algorithm is analyzed in an elaborate fashion. The logarithmic sum- product algorithm and the min-sum algorithm are two important variations of the sum-product algorithm. The logarithmic sum-product algorithm reduces multiplication to addition by introducing logarithmic likelihood ratio while the latter simplifies computation at the cost of precision.
Combination of OCR Engines for Page Segmentation Based on Performance Evaluation
Authors: M. Ferrer, E. Valveny
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

In this paper we present a method to improve the perfor- mance of individual page segmentation engines based on the combination of the output of several engines. The rules of combination are designed after analyzing the results of each individual method. This analysis is performed using a performance evaluation framework that aims at charac- terizing each method according to its strengths and weak- nesses rather than computing a single performance mea- sure telling which is the "best" segmentation method.
Multi-resolution Morse-Smale Complexes for Terrain Modeling
Authors: Emanuele Danovaro, Leila De Floriani, Maria Vitali
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

We propose a hierarchical representation for the morphology of a terrain. The basis of our morphological model is a decomposition of the terrain model, composed of the stable and unstable manifolds defined by its critical points, called a Morse-Smale complex. We propose a compact dual representation of the Morse-Smale complex and we define new simplification operators of the terrain morphology, which act on such representation. Based on these operators, we define a hierarchical morphology-based representation for a terrain, that we call a Multi-resolution Morse-Smale Complex (MMSC). Results from our implementation of the MMSC are shown.
An Improved Semantic Smoothing Model for Model-Based Document Clustering
Authors: Jiarong Cai, Yubao Liu, Jian Yin
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Recently, semantic smoothing is proposed as an efficient solution for the improvement of document cluster quality. However, the existing semantic smoothing model is not effective for partitional clustering to enhance the document clustering quality. In this paper, inspired by the TF*IDF schema and background elimination strategy, we first introduce an improved semantic smoothing model, which is suitable for both agglomerative and partitional clustering. Based on the improved semantic smoothing model, two model-document clustering algorithms, the partitional clustering algorithm and the agglomerative clustering algorithm, are also presented. The experimental results show our algorithms are more effective than the previous methods to improve the cluster quality.
The evolutionary potential of single-mode optical fibre systems
Authors: A. P. Mcdonna, D. B. Mortimore
Venue: BT Technology Journal (2007)

Single-mode optical fibre systems presently being installed in the BT network are primarily operating at 140 Mbit/s and 1.3 µm wavelength. There is scope for increasing the information capacity of these installed systems by both electrical and optical techniques. Three feasible upgrade options will be discussed and results of experiments performed at British Telecom Research Laboratories (BTRL) presented.
Structuring connections between content delivery servers groups
Authors: Jaime Lloret, Carlos Palau, Manuel Esteve
Venue: Future Generation Computer Systems (2008)

Content Delivery Servers can be grouped into logical networks according to several criteria: similar characteristics; functionalities; type of data delivered or proximity. Sometimes, it could be useful to find a way to join these autonomous logical networks. Research in this area focuses in centralized solutions, e.g. using a single point for data delivery between these groups. This paper proposes a novel architecture to interconnect content delivery servers from different groups and explains how they establish logical connections. The topology of logical connections, between servers clustered in different groups, changes depending on their capacity or because of server failures. The proposal is based on a hierarchical structure, in which the role of the server in the architecture is given by several parameters, being also scalable and fault-tolerant. We present the analytical model for this interconnection architecture and results obtained for some defined parameters. Finally, developed an application which used the protocol described in this paper and we deployed the proposed architecture in a real environment to obtain accurate measurements.
MateOnLine: web application to use mathematica locally
Authors: Javier Bilbao, Eugenio Bravo, Purificación González, Javier Chicote
Venue: Informatics in education (2007)

A web application has been developed using the Microsoft .NET technology, which allows to use the Mathematica software from any personal computer connected to Internet. It is not necessary to have the Mathematica software in the own computer, therefore the requirements ale limited to have a web browser. All the power of a high level package for numerical and symbolic calculation can be used with no need to spend great amounts of money in individual licenses. This allows students to use this software from their houses, by means of a simple interface, in any subject or project with mathematical calculations, even to attend virtual laboratories.
Automated Generation of Cross-System Software for Microcomputers
Authors: G. R. Johnson
Venue: Computer (1977)

GEN is a set of Fortran program writer modules designed to generate microcomputer assemblers and simulators. It is simple enough to be used by those with limited architecture and programming backgrounds yet flexible and powerful enough to generate efficient and well-structured assemblers and simulators for microcomputes sophisticated tectures and instruction sets. This paper describes the generating system, the generated gPoassemblers and simulators, and the advantages they offer in both programming and pedagogical applications.
GMSolid: Interactive Modeling for Design and Analysis of Solids
Authors: J. W. Boyse
Venue: IEEE Computer Graphics and Applications (1982)

In GMSolid, designers can work directly with primitives to build complex solids. This and GMSolid's friendliness, flexibility, and 3-D feel make it superior to wireframe CAD tools.
Hardware architecture for a general regression neural network coprocessor
Authors: Jesús Lázaro, Jagoba Arias, Armando Astarloa, Unai Bidarte, Aitzol Zuloaga
Venue: Neurocomputing (2007)

This article presents a series of hardware implementations of a general regression neural network (GRNN) using FPGAs. The paper describes the study of this neural network using different fixed and floating point implementations. The implementation includes training as well as testing of the network. It is focused on precision loss and area and speed results of the resulting neural network coprocessor that can be used in a System on Programmable Chip. A GRNN is able to approximate functions and it has been used in control, prediction, fault diagnosis, engine management among others. They are mainly implemented as software entities because they require a great amount of complex mathematical operations. With the increasing power and capabilities of current FPGAs, now it is possible not only to translate them into hardware but, due to the reconfigurable feature of these devices, to explore different hardware/software partitions as well. These hardware implementations increase both the speed and performance of these neural networks and the designer can select the area-speed trade-off that best fits the application.
Experimental evaluation of a coarse-grained switch scheduler
Authors: Charlie Wiseman, Jon Turner, Ken Wong, Brandon Heller
Venue: Proceedings of the 3rd ACM/IEEE Symposium on Architecture for networking and communications systems (2007)

Modern high performance routers rely on sophisticated interconnection networks to meet ever increasing demands on capacity. Previous studies have used a combination of analysis and idealized simulations to show that coarse-grained scheduling of traffic flows can be effective in preventing interconnect congestion while ensuring high utilization. In this work, we study the performance of a coarse-grained scheduler in a real router with a scalable architecture similar to those found in high performance commercial systems. Our results are obtained by taking fine-grained measurements within the router that provide a detailed picture of the scheduler's behavior under a variety of conditions, giving a more complete and realistic understanding of the short time-scale dynamics than previous studies could provide.
A Hierarchical Segmentation Algorithm Based on Mumford and Shah Model
Authors: Zhang Yingjie, Ge Liling
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

This paper proposes a new hierarchical segmentation algorithm. Comparing with the previous work, the segmentation procedure is divided into two steps: a pre-segmenting stage and a tuning stage. By this way, some difficulties like the initialization of the level set and converging to local minima can be completely eliminated. To find an initial segmentation that will be applied as initial contours for tuning, a novel edge detection algorithm is introduced at the pre-segmenting stage, which is implemented based on the Mumford and Shah model in level set frame. Due to the contours obtained with the properties of level set functions, many active contour approaches may be used for tuning at second stage. However, aim at segmenting noisy images, only the piecewise smooth Mumford and Shah approach is taken into consideration in this paper. The resulting algorithm has been demonstrated by several cases.
Indexing Historical Documents by Word Shape Signatures
Authors: J. Llados, G. Sanchez
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

In this paper a word spotting approach to index archival image documents is presented. Indices are constructed from keyword images. The spotting strategy is formulated on an indexing-by-shape basis. The well known shape context de- scriptor is used to compute word image signatures from the skeleton points. Afterwards, codewords are extracted from thresholded shape contexts. It is a simpler and more com- pact representation based on bit vectors. Document images are roughly segmented into words and a lookup table is con- structed. Each word subimage is taken as a bin. Keyword images are spotted into documents by a voting strategy con- sisting in indexing into the lookup table by codewords, and voting into the corresponding bins. The approach is illus- trated by a real application scenario consisting of docu- ments from a digital archive of the Spanish Civil War.
Search Engines that Learn from Implicit Feedback
Authors: Thorsten Joachims, Filip Radlinski
Venue: Computer (2007)

Search-engine logs provide a wealth of information that machine-learning techniques can harness to improve search quality. With proper interpretations that avoid inherent biases, a search engine can use training data extracted from the logs to automatically tailor ranking functions to a particular user group or collection.
Flow of water in rigid solids: Development and experimental validation of models for tests on asphalts
Authors: Filippo G. Praticò, Antonino Moro
Venue: Computers Mathematics with Applications (2008)

The goal of this paper is confined to the derivation of an equation for the analysis of the phenomenon of water flows along an asphalt pavement. By referring to the general theory for the percolation of water in rigid porous materials, we propose the theoretical derivation of models for some tests on asphalts. In order to validate the formalized models and to analyze the relationships among the main indicators introduced, in-field experiments were designed and performed. As our main results, we develop a model for tests on asphalts and validate it partially by means of our experimental results.