ppxscal/embedding_network huggingface dataset:
Compiling PCRE to FPGA for accelerating SNORT IDS
Authors: Abhishek Mitra, Walid Najjar, Laxmi Bhuyan
Venue: Proceedings of the 3rd ACM/IEEE Symposium on Architecture for networking and communications systems (2007)

Deep Payload Inspection systems like SNORT and BRO utilize regular expression for their rules due to their high expressibility and compactness. The SNORT IDS system uses the PCRE Engine for regular expression matching on the payload. The software based PCRE Engine utilizes an NFA engine based on certain opcodes which are determined by the regular expression operators in a rule. Each rule in the SNORT ruleset is translated by PCRE compiler into an unique regular expression engine. Since the software based PCRE engine can match the payload with a single regular expression at a time, and needs to do so for multiple rules in the ruleset, the throughput of the SNORT IDS system dwindles as each packet is processed through a multitude of regular expressions. In this paper we detail our implementation of hardware based regular expression engines for the SNORT IDS by transforming the PCRE opcodes generated by the PCRE compiler from SNORT regular expression rules. Our compiler generates VHDL code corresponding to the opcodes generated for the SNORT regular expression rules. We have tuned our hardware implementation to utilize an NFA based regular expression engine, using greedy quantifiers, in much the same way as the software based PCRE engine. Our system implements a regular expression only once for each new rule in the SNORT ruleset, thus resulting in a fast system that scales well with new updates. We implement two hundred PCRE engines based on a plethora of SNORT IDS rules, and use a Virtex-4 LX200 FPGA, on the SGI RASC RC 100 Blade connected to the SGI ALTIX 4700 supercomputing system as a testbed. We obtain an interface through-put of (12.9 GBits/s) and also a maximum speedup of 353X over software based PCRE execution.
Selective shielding: a crosstalk-free bus encoding technique
Authors: Madhu Mutyam
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

With CMOS process technology scaling to deep submicron level, propagation delay across long on-chip buses is becoming one of the main performance limiting factors in high-performance designs. Propagation delay is very significant when adjacent wires are transitioning in opposite direction (i.e., crosstalk transitions) as compared to transitioning in the same direction. As crosstalk transitions have significant impact on propagation delay, several bus encoding techniques have been proposed in literature to eliminate such transitions. In this work, we propose a technique, namely, selective shielding, to eliminate crosstalk transitions. Compared to the conventional shielding technique, our technique significantly reduces the number of extra wires. We give a lower bound on the number of wires required to encode n-bit data using the selective shielding technique. We show that our technique achieves better energy savings and requires less area as compared to the other techniques.
The Evaluation Study of Knowledge Management Performance Based on Grey -AHP Method
Authors: Fang Jin, Peide Liu, Xin Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

The Knowledge management will become important and effective strategic instrument to improve the organizational competitive power with the coming of knowledge-economy's age, the evaluation of knowledge management performance is an important part of knowledge management process and an important way to know the level of knowledge management of enterprise. This paper brings forward the indicator system of knowledge management's performance evaluation on the basis of current study of home and oversea and the related reference, and establishes the performance evaluation model based on combination of Grey Evaluation Method and AHP method(Grey-AHP), and also do some example research. The examples demonstrated that: Grey-AHP method can do well in evaluation.
On the performance of bitmap indices for high cardinality attributes
Authors: Kesheng Wu, Ekow Otoo, Arie Shoshani
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

It is well established that bitmap indices are efficient for read-only attributes with low attribute cardinalities. For an attribute with a high cardinality, the size of the bitmap index can be very large. To overcome this size problem, specialized compression schemes are used. Even though there are empirical evidences that some of these compression schemes work well, there has not been any systematic analysis of their effectiveness. In this paper, we systematically analyze the two most efficient bitmap compression techniques, the Byte-aligned Bitmap Code (BBC) and the Word-Aligned Hybrid (WAH) code. Our analyses show that both compression schemes can be optimal. We propose a novel strategy to select the appropriate algorithms so that this optimality is achieved in practice. In addition, our analyses and tests show that the compressed indices are relatively small compared with commonly used indices such as B-trees. Given these facts, we conclude that bitmap index is efficient on attributes of low cardinalities as well as on those of high cardinalities.
Towards heterogeneous robot teams for disaster mitigation: Results and performance metrics from RoboCup rescue: Field Reports
Authors: Stephen Balakirsky, Stefano Carpin, Alexander Kleiner, Michael Lewis, Arnoud Visser, Jijun Wang, Vittorio Amos Ziparo
Venue: Journal of Field Robotics (2007)

Urban Search and Rescue is a growing area of robotic research. The RoboCup Federation has recognized this, and has created the new Virtual Robots competition to complement its existing physical robot and agent competitions. In order to successfully compete in this competition, teams need to field multi-robot solutions that cooperatively explore and map an environment while searching for victims. This paper presents the results of the first annual RoboCup Rescue Virtual competition. It provides details on the metrics used to judge the contestants as well as summaries of the algorithms used by the top four teams. This allows readers to compare and contrast these effective approaches. Furthermore, the simulation engine itself is examined and real-world validation results on the engine and algorithms are offered. &copy; 2007 Wiley Periodicals, Inc.
QBD approximations of a call center queueing model with general patience distribution
Authors: Ken'ichi Kawanishi
Venue: Computers and Operations Research (2008)

This paper investigates a computationally practical way for analyzing a call center queueing model, i.e., a finite-capacity, multi-server queueing model, where each server goes on a single vacation. Poisson arrival process and exponential service and vacation times are assumed. We also assume that each customer may leave the queue due to impatience. Customers' patience times are i.i.d. random variables with a general distribution. Level-dependent finite QBD (quasi-birth-death) processes are employed to approximate such a queueing model. Two approaches are considered. The first one uses the phase-type (PH) distribution to approximate the general patience distribution, whereas the second one is based on the idea of replacing the eventual reneging of customers with balking. We find that the first approach is almost impossible to compute numerically due to the exponential growth of the size of the block matrices in a level-dependent finite QBD. We examine the validity and applicability of the approximation based on the second approach and show that it gives us a practical way to obtain performance measures of call center systems in practical scale with sufficiently reasonable accuracy.
Relation extraction and the influence of automatic named-entity recognition
Authors: Claudio Giuliano, Alberto Lavelli, Lorenza Romano
Venue: ACM Transactions on Speech and Language Processing (TSLP) (2007)

We present an approach for extracting relations between named entities from natural language documents. The approach is based solely on shallow linguistic processing, such as tokenization, sentence splitting, part-of-speech tagging, and lemmatization. It uses a combination of kernel functions to integrate two different information sources: (i) the whole sentence where the relation appears, and (ii) the local contexts around the interacting entities. We present the results of experiments on extracting five different types of relations from a dataset of newswire documents and show that each information source provides a useful contribution to the recognition task. Usually the combined kernel significantly increases the precision with respect to the basic kernels, sometimes at the cost of a slightly lower recall. Moreover, we performed a set of experiments to assess the influence of the accuracy of named-entity recognition on the performance of the relation-extraction algorithm. Such experiments were performed using both the correct named entities (i.e., those manually annotated in the corpus) and the noisy named entities (i.e., those produced by a machine learning-based named-entity recognizer). The results show that our approach significantly improves the previous results obtained on the same dataset.
Efficient On-Line Proofs of Equalities and Inequalities of Formulas
Authors: H. Samet
Venue: IEEE Transactions on Computers (1980)

An algorithm is presented for proving equivalence and inequivalence of instances of formulas involving constant terms. It is based on the construction of an equality data base in the form of a grammar. The algorithm differes from other approaches to the problem by being an on-line algorithm. Equality between two formulas can be proved in time proportional to the number of constant and function symbols appearing within them. An algorithm is also given for updating the equality data base. It has a worse case running time which is proportional to the square of the number of different formulas previously encountered.
A New Position-Based Routing Protocol for Reducing the Number of Exchanged Route Request Messages in Mobile Ad-hoc Networks
Authors: S. Kalhor, M. Anisi, A. T. Haghighat
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

Mobile Ad-hoc network is a network of mobile nodes that within, the mobile nodes, communicate through almost slow links. In an Ad-hoc network, two nodes can communicate with each other if their distance became lower than the minimum of their transmission range. So, sending message between two nodes in such network may need routing between intermediate nodes, therefore, a specific route between such nodes should be considered. In this paper, the reasons of route breakage which are recognized by Location Aided Routing (LAR) protocol will be studied and in the following, we propose a new routing protocol that will reduce the number of exchanged route request messages. Our experimental results show that by using this protocol, the number of nodes which participate in routing operation and also the average time of route discovery will be reduced, considerably.
GAWDN-NFIS: Neural-Fuzzy Inference System with a Genetic Algorithm Based on Weighted Data Normalization and Its Application in Medicine
Authors: Qun Song, Tianmin Ma
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

This paper introduces an approach of Neural Fuzzy Inference System (NFIS) with a Genetic Algorithm (GA) based on Weighted Data Normalization (WDN) and its application in a medical decision support system. The WDN method optimizes the data normalization ranges for the input variables of the neural fuzzy inference system and a genetic algorithm is used as part of the WDN method. A steepest descent algorithm (BP) is used for NFIS learning on the normalized data set. The derived weights have the meaning of feature importance and can be used for feature selection to decrease the number of input variables. The GAWDN-NFIS is illustrated on the case study: a real medical decision support problem of estimating the survival of haemodialysis patients. This approach can also be applied to other distance-based, prototype learning neural network or fuzzy inference models.
The Risk-Evaluation Model in Customs Based on BP Neural Networks
Authors: Feng Ye, Gengui Zhou, Jinqiu Lu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

The basic learning algorithm of BP neural network based on delta learning rule is introduced, and the Levengberg-Marquardt algorithm is described. Then the BP neural network model of risk-evaluation in China Customs is presented. It includes the design of the input layer, the output layer and the hidden layer and the confirmation of the initial weights and the learning rate. On the basis of the data warehouse of risk management of China Customs, The BP neural network of the risk-evaluation is implemented, and the comparison of performance between the momentum factorial algorithm and the Levenberg-Marquardt algorithm is indicated. At last, the further application of BP neural network in China Customs is discussed.
Commonalities in Risk Management and Agile Process Models
Authors: Jaana Nyfjord, Mira Kajko-Mattsson
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

On the surface, agile and risk management process models seem to constitute two contrasting approaches. Risk management follows a heavyweight approach whereas agile process models oppose it. In this paper, we identify commonalities in these two process models. Our results show that they have much in common, and that a merge between them is possible.
DFR: A New Improved Algorithm for Mining Frequent Itemsets
Authors: Sheng Chai, Hai-Chun Wang, Ji-Fan Qiu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

Efficiency has been concerned in the research of association rules mining. This paper presents an improved method called Direct-Fined-Remove (DFR) algorithm to mine a database consisting of remove and direct steps. When pruning the candidates itemsets, the algorithm eliminate non-frequent subset of candidates in the remove steps. In the direct steps, the algorithm directly generates the frequent itemsets by computing and comparing the frequency of frequent k-itemsts with k in the meantime. The contributions include: (1) proposes an algorithm to raise the probability of obtaining information in scanning database and reduce the potential scale of itemsets. (2) successfully applies the proposed algorithm to the Teaching Evaluation System to determine characteristics of good teaching effect. Experiments show that the probability which grade point of associate professor being more than 90 is 35%, the support degree is 40%, and the probability which grade point of bachelor being more than 90 is 16%, the support degree is 83%.
A High Compression and Short Test Sequence Test Compression Technique to Enhance Compressions of LFSR Reseeding
Authors: Seongmoon Wang, Wenlong Wei, Srimat T. Chakradhar
Venue: Proceedings of the 16th Asian Test Symposium (2007)

This paper presents a test data compression scheme that can be used to further improve compressions achieved by LFSR reseeding. The proposed compression technique can be implemented with very low hardware overhead. Unlike most commercial test data compression tools, the proposed method requires no special ATPG that is customized for the proposed scheme and can be used to compress test patterns generated by any ATPG tool. The test data to be stored in the ATE memory are much smaller than that for previously published schemes and the number of test patterns that need to be generated is smaller than other weighted random pattern testing schemes. Experimental results on a large industry design show that over 1600X compression is achievable by the proposed scheme with the number of patterns comparable to that of highly compacted deterministic patterns.
Simplifying fault diagnosis in locally managed rural WiFi networks
Authors: Sonesh Surana, Rabin Patra, Eric Brewer
Venue: Proceedings of the 2007 workshop on Networked systems for developing regions (2007)

The last three years have seen a lot of work in making WiFi-enabled Long Distance (WiLD) networking a reality in rural areas. Generally these networks are managed by non-local users who cannot guarantee long term support beyond a pilot. For long term operational sustainability, it is essential that maintenance duties be transferred to local administrators. In this paper, we argue that the research agenda should expand into areas of simplified diagnosis solutions as an en-abler for locally managed WiLD networks. Motivated by real faults we have seen in our own deployment at the Aravind Eye Hospital, we propose a framework to simplify diagnosis and show some initial results towards this direction.
ZIL: an implementation of Lisp on MVS/XA at C. S. Draper laboratory
Authors: Stephen E. Bacher
Venue: ACM SIGPLAN Lisp Pointers (1987)

"ZIL" is an implementation of Lisp on MVS/XA running on an IBM 3090-200 System/370 mainframe at the Charles Stark Draper Laboratory. The system includes a full Lisp interpreter and compiler, as well as a full-screen dialog user interface developed in IBM's ISPF (Interactive System Productivity Facility) product.
Model of electrostatic actuated deformable mirror using strongly coupled electro-mechanical finite element
Authors: Véronique Rochus, Jean-Claude Golinval, Christophe Louis, Carlos Mendez, Igor Klapka
Venue: Analog Integrated Circuits and Signal Processing (2007)

The aim of this paper is to deal with multi-physics simulation of micro-electro-mechanical systems (MEMS) based on an advanced numerical methodology. MEMS are very small devices in which electric as well as mechanical and fluid phenomena appear and interact. Because of their microscopic scale, strong coupling effects arise between the different physical fields, and some forces, which were negligible at macroscopic scale, have to be taken into account. In order to accurately design such micro-electro-mechanical systems, it is of primary importance to be able to handle the strong coupling between the electric and the mechanical fields. In this paper, the finite element method (FEM) is used to model the strong coupled electro-mechanical interactions and to perform static and transient analyses taking into account large mesh displacements. These analyses will be used to study the behaviour of electrostatically actuated micro-mirrors.
Seed-Relative Segmentation Robustness of Watershed and Fuzzy Connectedness Approaches
Authors: Romaric Audigier, Roberto Lotufo
Venue: Proceedings of the XX Brazilian Symposium on Computer Graphics and Image Processing (2007)

This paper analyzes the robustness issue in three segmentation approaches: the iterative relative fuzzy object extraction, the watershed transforms (WT) by image foresting transform and by minimum spanning forest. These methods need input seeds, which can be source of variability in the segmentation result. So, the robustness of these segmentation methods in relation to the input seeds is focused. The core of each seed is defined as the region where the seed can be moved without altering the segmentation result. We demonstrate that the core is identical for the three methods providing that the tie-zone transform has previously been applied on these methods. Indeed, as the two WT approaches do not return unique solution, the set of possible solutions has to be considered in a unified solution. So does the tie-zone transform. As opposed to what we could think, we show that the core is included in but different from the catchment basin. We also demonstrate that the tie-zone transforms of these WTs are always identical. Furthermore, the framework of minimal sets of seeds, an inverse problem of segmentation, is extended to the pixel level and related to the cores. A new algorithm for the computation of minimal seed sets is finally proposed.
Invariant theory for singular α-determinants
Authors: Kazufumi Kimoto, Masato Wakayama
Venue: Journal of Combinatorial Theory Series A (2008)

From the irreducible decompositions' point of view, the structure of the cyclic GL"n(C)-module generated by the @a-determinant degenerates when @a=+/-1k(1=
MSP: multi-sequence positioning of wireless sensor nodes
Authors: Ziguo Zhong, Tian He
Venue: Proceedings of the 5th international conference on Embedded networked sensor systems (2007)

Wireless Sensor Networks have been proposed for use in many location-dependent applications. Most of these need to identify the locations of wireless sensor nodes, a challenging task because of the severe constraints on cost, energy and effective range of sensor devices. To overcome limitations in existing solutions, we present a Multi-Sequence Positioning (MSP) method for large-scale stationary sensor node localization in outdoor environments. The novel idea behind MSP is to reconstruct and estimate two-dimensional location information for each sensor node by processing multiple one-dimensional node sequences, easily obtained through loosely guided event distribution. Starting from a basic MSP design, we propose four optimizations, which work together to increase the localization accuracy. We address several interesting issues, such as incomplete (partial) node sequences and sequence flip, found in the Mirage test-bed we built. We have evaluated the MSP system through theoretical analysis, extensive simulation as well as two physical systems (an indoor version with 46 MICAz motes and an outdoor version with 20 MICAz motes). This evaluation demonstrates that MSP can achieve an accuracy within one foot, requiring neither additional costly hardware on sensor nodes nor precise event distribution. It also provides a nice tradeoff between physical cost (anchors) and soft cost (events), while maintaining localization accuracy.
Robust Object Tracking Via Online Dynamic Spatial Bias Appearance Models
Authors: Datong Chen, Jie Yang
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a human vision system during object tracking, we propose to partition an object into regions with difierent confidences and track the object using a dynamic spatial bias appearance model (DSBAM) estimated from region confidences. The confidence of a region is estimated to re ect the discriminative power of the region in a feature space, and the probability of occlusion. We propose a novel hierarchical Monte Carlo (HAMC) algorithm to learn region confidences dynamically in every frame. The algorithm consists of two levels of Monte Carlo processes implemented using two particle filtering procedures at each level and can effciently extract high confidence regions through video frames by exploiting the temporal consistency of region confidences. A dynamic spatial bias map is then generated from the high confidence regions, and is employed to adapt the appearance model of the object and to guide a tracking algorithm in searching for correspondences in adjacent frames of video images. We demonstrate feasibility of the proposed method in video surveillance applications. The proposed method can be combined with many other existing tracking systems to enhance the robustness of these systems.