ppxscal/embedding_network huggingface dataset:
Abstracting Symbolic Execution with String Analysis
Authors: Daryl Shannon, Sukant Hajra, Alison Lee, Daiqian Zhan, Sarfraz Khurshid
Venue: Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (2007)

Forward symbolic execution is a technique for program analysis that explores the execution paths of a program by maintaining a symbolic representation of the program state. Traditionally, applications of this technique have focused on symbolically representing only primitive data types, while more recent extensions have expanded to reference types. We demonstrate the ability to symbolically execute a commonly used library class, specifically a string, at an abstract level. By abstracting away the implementation details of strings using finite-state automata, symbolic execution can scale to more complex programs. This technique can be applied to programs which generate complicated strings, such as SQL database queries.
Scheduling of conflicting refactorings to promote quality improvement
Authors: Hui Liu, Ge Li, Zhiyi Ma, Weizhong Shao
Venue: Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering (2007)

Software refactoring is to restructure object-oriented software to improve its quality, especially extensibility, reusability and maintainability while preserving its external behaviors. For a special software system, there are usually quite a few refactorings available at the same time. But these refactorings may conflict with each other. In other words, carrying out a refactoring may disable other refactorings. Consequently, only a subset of the available refactorings can be applied together, and which refactorings will be applied depends on the schedule (application order) of the refactorings. Furthermore, carrying out different subsets of the refactorings usually leads to different improvement of software quality. As a result, in order to promote the improvement of software quality, refactorings should be scheduled rationally. However, how to schedule refactorings is rarely discussed. Usually, software engineers carry out refactorings immediately when they are found out. They do not wait until all applicable refactorings are found out and scheduled. In other words, the refactorings are not scheduled explicitly, and conflicts among them are not taken into consideration. Though more and more refactorings are formalized and automated by refactoring tools, refactoring tools apply refactorings usually in a nondeterministic fashion (in random). In this paper, we propose a scheduling approach to schedule conflicting refactorings to promote the improvement of software quality achieved by refactorings. Conflicts among refactorings are detected, and then a scheduling model is presented. And then a heuristic algorithm is proposed to solve the scheduling model. Results of experiments suggest that the proposed scheduling approach is effective in promoting the improvement of software quality
Web 2.0 Creates Security Challenges
Authors: George Lawton
Venue: Computer (2007)

While Web 2.0's interactivity has made it very popular with users and Web site operators, the technology is also increasingly popular with hackers.
Large-Margin Discriminative Training of Hidden Markov Models for Speech Recognition
Authors: Dong Yu, Li Deng
Venue: Proceedings of the International Conference on Semantic Computing (2007)

Discriminative training has been a leading factor for improving automatic speech recognition (ASR) performance over the last decade. The traditional discriminative training, however, has been aimed to minimize empirical error rates on training sets, which may not be well generalized to test sets. Many attempts have been made recently to incorporate the principle of large margin (PLM) into the training of hidden Markov models (HMMs) in ASR to improve the generalization abilities. Significant error rate reduction on the test sets has been observed on both small vocabulary and large vocabulary continuous ASR tasks using large-margin discriminative training (LMDT) techniques. In this paper, we introduce the PLM, define the concept of margin in the HMMs, and survey a number of popular LMDT algorithms proposed and developed recently. Specifically, we review and compare the large-margin minimum classification error (LM-MCE) estimation, soft-margin estimation (SME), large margin estimation (LME), large relative margin estimation (LRME), and large margin training (LMT) with a focus on the insights, the training criteria, the optimization techniques used, and the strengths and weaknesses of these different approaches. We suggest future research directions in our conclusion of this paper.
Ground-based sensing system for weed mapping in cotton
Authors: Ruixiu Sui, J. Alex Thomasson, James Hanks, James Wooten
Venue: Computers and Electronics in Agriculture (2008)

A ground-based weed mapping system was developed to measure weed intensity and distribution in a cotton field. The weed mapping system includes WeedSeeker^(R) PhD600 sensor modules to indicate the presence of weeds between rows, a GPS receiver to provide spatial information, and a data acquisition and processing unit to collect and process the weed data and spatial information. The PhD600 sensor module is a commercial product used as a component in this weed mapping system. A prototype of the weed mapping system was field evaluated for 2 years. The system performed well during the field evaluation. Weed intensity in the field was also estimated based on remotely sensed imagery, and these estimates were used to create weed maps. Development of the weed mapping system and its evaluation results are reported in this article.
Neighbors-on-Path: A New Selection Strategy for On-Chip Networks
Authors: G. Ascia, V. Catania, M. Palesi, D. Patti
Venue: Proceedings of the 2006 IEEE/ACM/IFIP Workshop on Embedded Systems for Real Time Multimedia (2006)

Efficient and deadlock-free routing is critical to the performance of networks-on-chip. In this paper we present an approach that can be coupled to any adaptive routing algorithm to improve the performance with a minimal overhead on area and energy consumption. The proposed approach introduces the concept of neighbors-on-path to exploit the situations of indecision occurring when the routing function returns several admissible output channels. A selection strategy is developed with the aim to choose the channel that will allow the packet to be routed to its destination along a path that is as free as possible of congested nodes. Performance evaluation is carried out by using a flit-accurate simulator on traffic scenarios generated by both synthetic and real applications. Results obtained show how the proposed selection policy applied to the odd-even routing algorithm outperforms other deterministic and adaptive routing algorithms both in average delay and energy consumption
An efficient model predictive controller with pole placement
Authors: Qun-Liang Zhang, Yu-Geng Xi
Venue: Information Sciences: an International Journal (2008)

For model predictive control (MPC) of constrained systems, enlarging the feasible region is usually in conflict with improving the dynamic performance. To resolve the conflict, we proposed an efficient model predictive controller with pole placement for a class of discrete-time linear systems. By specifying a group of circular regions that contain the desired closed-loop poles, appropriate terminal weighting matrices and local controllers are calculated to construct a time-varying terminal convex set, which is a significant constraint for the online optimization problem. During the online optimization, the size of the terminal convex set can adjust itself according to the actual state at each sampling time. In this way, a large initial feasible region can be achieved while maintaining the good dynamic performance. An illustrative example is used to show the effectiveness of the proposed approach.
How to achieve (some) balance in anti-circumvention laws
Authors: Pamela Samuelson, Jerome H. Reichman, Graeme Dinwoodie
Venue: Communications of the ACM (2008)

Should users of technically protected content be able to give notice and require content owners to take down the technical measure to enable fair uses?
A goodness-of-fit test for normality based on polynomial regression
Authors: Daniele Coin
Venue: Computational Statistics Data Analysis (2008)

Statistical models are often based on normal distributions and procedures for testing such distributional assumption are needed. Many goodness-of-fit tests are available. However, most of them are quite insensitive in detecting non-normality when the alternative distribution is symmetric. On the other hand all the procedures are quite powerful against skewed alternatives. A new test for normality based on a polynomial regression is presented. It is very effective in detecting non-normality when the alternative distribution is symmetric. A comparison between well known tests and this new procedure is performed by simulation study. Other properties are also investigated.
Requirements and Services for Metadata Management
Authors: Paolo Missier, Pinar Alper, Oscar Corcho, Ian Dunlop, Carole Goble
Venue: IEEE Internet Computing (2007)

Knowledge-intensive applications pose new challenges to metadata management, including distribution, access control, uniformity of access, and evolution in time. The authors identify general requirements for metadata management and describe a simple model and service that focuses on RDF metadata to address these requirements.
Throughput Guaranteed Restorable Routing Without Traffic Prediction
Authors: M. Kodialam, T. Lakshman, Sudipta Sengupta
Venue: Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols (2006)

Two-phase routing, where traffic is first distributed to intermediate nodes before being routed to the final destination,has been recently proposed [10], [11], [18] for handling widely fluctuating traffic without the need to adapt network routingto changing traffic. Pre-configuring the network in a traffic independent manner using two-phase routing simplifies networkoperation considerably. In this paper, we extend this routing scheme by providing resiliency against link failures throughtwo different fast restoration mechanisms ¿ local (link/span) based and end-to-end (path) based. We view this as importantprogress towards adding carrier-class reliability to the robustness of the scheme so as to facilitate its future deploymentin Internet Service Provider (ISP) networks. The main contribution of the paper is the development of fast combinatorial algorithmsfor routing under the scheme with link and path restoration mechanisms so as to minimize the maximum utilization of any linkin the network, or equivalently, maximize the throughput. The algorithms developed are Fully Polynomial Time ApproximationSchemes (FPTAS) ¿ for any given ¿ > 0, an FPTAS guarantees a solution that is within a (1 + ¿)-factor of the optimum and runsin time polynomial in the input size and 1/¿. To the best of our knowledge, this is the first work in the literature thatconsiders making the scheme resilient to link failures through pre-provisioned fast restoration mechanisms. We evaluate theperformance of link and path restoration (in terms of throughput) and compare it with that of unprotected routing.
Using the Google web toolkit to create SCORM 2004 compliant online tests
Authors: Anja Kronawitter, Jan-Torsten Milde
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

This paper describes how to generate the content and interactive online tests of SCORM 2004 E-Learning units. The generation process is split into two phases. First the content is structurally anntoted with OpenOffice. The resulting XML files are transformed into SCORM 2004 compliant modules, that are finally deployed to the LMS. A GWT based widget library for the creation of online tests has been developed.
A Computational Model of Korean Lexical Decision Task and Its Comparative Analysis by Using Connectionist Model
Authors: Kinam Park, Kigon Lyu, Wonhee Yu, Heuiseok Lim
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

In this paper, we experimented word frequency effect, word similarity effect and semantic priming effect among many language phenomena appears when Lexical Decision Task is progressing independently of language by applying them to 2 syllable words of Korean language through human being and connectionist model, and we compared and analyzed the result. The experiment shows that there were word frequency effect, word similarity effect and semantic prim- ing effect for each human being and connectionist model and, the results of experiment behavioral and connectionist model exposed meaningful similarity.
A Matrix Formalism for Asynchronous Implementation of Algorithms
Authors: A. Thayse
Venue: IEEE Transactions on Computers (1984)

We show that well-known instructions such as if then else, fork, join, while do, can be represented as row matrices or column-matrices. We define a matrix-instruction which encompasses and generalizes the above instructions. This instruction provides us with a compact tool for describing algorithms and for synthesizing them in synchronous and asynchronous structures. We show, e.g., that the synthesis of a program by means of elementary instructions reduces to the factorization of a matrix into elementary matrices. A formalism and a computation method are introduced which generalize the author's previous work on the subject.
Learning to Classify Ordinal Data: The Data Replication Method
Authors: Jaime S. Cardoso, Joaquim F. Pinto da Costa
Venue: The Journal of Machine Learning Research (2007)

Classification of ordinal data is one of the most important tasks of relation learning. This paper introduces a new machine learning paradigm specifically intended for classification problems where the classes have a natural order. The technique reduces the problem of classifying ordered classes to the standard two-class problem. The introduced method is then mapped into support vector machines and neural networks. Generalization bounds of the proposed ordinal classifier are also provided. An experimental study with artificial and real data sets, including an application to gene expression analysis, verifies the usefulness of the proposed approach.
Modeling pairwise key establishment for random key predistribution in large-scale sensor networks
Authors: Dijiang Huang, Manish Mehta, Appie van de Liefvoort, Deep Medhi
Venue: IEEE/ACM Transactions on Networking (TON) (2007)

Sensor networks are composed of a large number of low power sensor devices. For secure communication among sensors, secret keys are required to be established between them. Considering the storage limitations and the lack of post-deployment configuration information of sensors, RandomKey Predistribution schemes have been proposed. Due to limited number of keys, sensors can only share keys with a subset of the neighboring sensors. Sensors then use these neighbors to establish pairwise keys with the remaining neighbors. In order to study the communication overhead incurred due to pairwise key establishment, we derive probability models to design and analyze pairwise key establishment schemes for large-scale sensor networks. Our model applies the binomial distribution and a modified binomial distribution and analyzes the key path length in a hop-by-hop fashion. We also validate our models through a systematic validation procedure. We then show the robustness of our results and illustrate how our models can be used for addressing sensor network design problems.
Optimal Control of Two-Stage Discrete Event Systems with Real-Time Constraints
Authors: Jianfeng Mao, Christos G. Cassandras
Venue: Discrete Event Dynamic Systems (2007)

We consider discrete event systems (DES) involving tasks with real-time constraints and seek to control processing times so as to minimize a cost function subject to each task meeting its own constraint. When tasks are processed over a single stage, it has been shown that there are structural properties of the optimal sample path that lead to very efficient solutions of such problems. When tasks are processed over multiple stages and are subject to end-to-end real-time constraints, these properties no longer hold and no obvious extensions are known. We consider a two-stage problem with homogeneous cost functions over all tasks at each stage and derive several new optimality properties. These properties lead to the idea of introducing "virtual" deadlines at the first stage, thus partially decoupling the stages so that the known efficient solutions for single-stage problems can be used. We prove that the solution obtained by an iterative virtual deadline algorithm (VDA) converges to the global optimal solution of the two-stage problem and illustrate the efficiency of the VDA through numerical examples.
Development of intelligent multisensor surveillance systems with agents
Authors: Juan Pavón, Jorge Gómez-Sanz, Antonio Fernández-Caballero, Julián J. Valencia-Jiménez
Venue: Robotics and Autonomous Systems (2007)

Intelligent multisensor surveillance systems consist of several types of sensors, which are installed on fixed and mobile devices. These components provide a huge quantity of information that has to be contrasted, correlated and integrated in order to recognize and react on special situations. These systems work in highly dynamic environments, with severe security and robustness requirements. All these characteristics imply the need for distributed solutions. In these solutions, scattered components can decide and act with some degree of autonomy (for instance, if they become isolated), or cooperate and coordinate for a complete tracking of special situations. In order to cope with these requirements and to better structure the solution, we have decided to design surveillance system control as a multiagent system. This is done by applying an agent-orientated methodology, which is assessed with concrete scenarios.
A High Data-Rate Digital Output Correlator Design
Authors: K. W. Current
Venue: IEEE Transactions on Computers (1980)

A high data-rate digital output correlator integrated circuit design which uses new synchronous sequential quaternary threshold logic gates is proposed and compared to the all-binary equivalent realization of this function. Substantial integrated circuit device count and die area savings are projected for the multiple valued logic realization.
Document Processing via Trained Morphological Operators
Authors: N. Hirata
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

Morphological operators have proven to be useful for many image processing tasks. However, the design of an adequate operator for a given task is not simple in gen- eral. A possible approach to deal with this difficulty is to design operators using training based methods. This work shows the application of trained morphological operators for several document processing tasks including character recognition, text segmentation and graphics processing.
Satisfaction balanced mediation
Authors: Jorge-Arnulfo Quiané-Ruiz, Philippe Lamarre, Sylvie Cazalens, Patrick Valduriez
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

We consider a distributed information system that allows autonomous consumers to query autonomous providers. We focus on the problem of query allocation from a new point of view, by considering consumers and providers' satisfaction in addition to query load. We define satisfaction as a long-run notion based on the consumers and providers' preferences. We propose and validate a mediation process, called SBMediation, which is compared to Capacity based query allocation. The experimental results show that SBMediation significantly outperforms Capacity based when confronted to autonomous participants.
Configuration-Dependent Performance of a Prioritized CSMA Broadcast Network
Authors: W. B. Watson
Venue: Computer (1981)

The interaction of node placement and contention mechanism is crucial to network performance. These experiments suggest that elaborate contention schemes have but little advantage over simpler ones. 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
Comparing Genomes with Duplications: A Computational Complexity Point of View
Authors: Guillaume Blin, Cedric Chauve, Guillaume Fertin, Romeo Rizzi, Stephane Vialette
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2007)

In this paper, we are interested in the computational complexity of computing (dis)similarity measures between two genomes when they contain duplicated genes or genomic markers, a problem that happens frequently when comparing whole nuclear genomes. Recently, several methods ( [1], [2]) have been proposed that are based on two steps to compute a given (dis)similarity measure M between two genomes G_1 and G_2: first, one establishes a oneto- one correspondence between genes of G_1 and genes of G_2 ; second, once this correspondence is established, it defines explicitly a permutation and it is then possible to quantify their similarity using classical measures defined for permutations, like the number of breakpoints. Hence these methods rely on two elements: a way to establish a one-to-one correspondence between genes of a pair of genomes, and a (dis)similarity measure for permutations. The problem is then, given a (dis)similarity measure for permutations, to compute a correspondence that defines an optimal permutation for this measure. We are interested here in two models to compute a one-to-one correspondence: the exemplar model, where all but one copy are deleted in both genomes for each gene family, and the matching model, that computes a maximal correspondence for each gene family. We show that for these two models, and for three (dis)similarity measures on permutations, namely the number of common intervals, the maximum adjacency disruption (MAD) number and the summed adjacency disruption (SAD) number, the problem of computing an optimal correspondence is NP-complete, and even APXhard for the MAD number and SAD number.
Space-Efficient Keying in Wireless Communication Networks
Authors: Neeraj Mittal
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

We investigate the problem of assigning keys to nodes in a network such that each node is able to communicate with every other node in a secure manner. We propose a key as- signment scheme that assigns at most log n 2 keys to each node, where n is the number of nodes in the network. The key that two nodes should use to securely communicate with each other is derived from at most log n keys and can be computed in O(log n) time. Finally, the collusion resistance of our scheme degrades gracefully as the number of collud- ing nodes increase in contrast to a recently proposed key assignment scheme that has zero collusion resistance (that is, two colluding nodes can eavesdrop on all communica- tion in the network). To our knowledge, the key assignment scheme presented in this paper is the most efficient secure key assignment scheme in terms of space that has been pro- posed so far. Key words: secure communication, key pre-distribution, poly-logarithmic key assignment, complete bipartite graph, complete graph, collusion resistance