ppxscal/embedding_network huggingface dataset:
A Hybrid Approach to Distributed Constraint Satisfaction
Authors: David Lee, Inés Arana, Hatem Ahriz, Kit-Ying Hui
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

We present a hybrid approach to Distributed Constraint Satisfaction which combines incomplete, fast, penalty-based local search with complete, slower systematic search. Thus, we propose the hybrid algorithm PenDHyb where the distributed local search algorithm DisPeL is run for a very small amount of time in order to learn about the difficult areas of the problem from the penalty counts imposed during its problem-solving. This knowledge is then used to guide the systematic search algorithm SynCBJ. Extensive empirical results in several problem classes indicate that PenDHyb is effective for large problems.
Blind Source Separation in Post-nonlinear Mixtures Using Natural Gradient Descent and Particle Swarm Optimization Algorithm
Authors: Kai Song, Mingli Ding, Qi Wang, Wenhui Liu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Extracting independent source signals from their nonlinear mixtures is a very important issue in many realistic models. This paper proposes a new method for solving nonlinear blind source separation (NBSS) problems by exploiting particle swarm optimization (PSO) algorithm and natural gradient descent. First, we address the problem of separation of mutually independent sources in post-nonlinear mixtures. The natural gradient descent is used to estimate the separation matrix. Then we define the mutual information between output signals as the fitness function of PSO. The mutual information is used to measure the statistical dependence of the outputs of the demixing system. PSO can rapidly obtain the globally optimal coefficients of the higher order polynomial functions. Compared to conventional NBSS approaches, the main characteristics of this method are its simplicity, the rapid convergence and high accuracy. In particular, it is robust against local minima in search for inverse functions. Experiments are discussed to demonstrate these results.
Exception Handling in Context-Aware Agent Systems: A Case Study
Authors: Nelio Cacho, Karla Damasceno, Alessandro Garcia, Alexander Romanovsky, Carlos Lucena
Venue: Software Engineering for Multi-Agent Systems V: Research Issues and Practical Applications (2007)

Handling erroneous conditions in context-aware mobile agent systems is challenging due to their intrinsic characteristics: openness, lack of structuring, mobility, asynchrony and increased unpredictability. Even though several context-aware middleware systems now support the development of mobile agent-based applications, they rarely provide explicit and adequate features for context-aware exception handling. This paper reports our experience in implementing error handling strategies in some prototype context-aware collaborative applications built with the MoCA (Mobile Collaboration Architecture) system. MoCA is a publish-subscribe middleware supporting the development of collaborative mobile applications by providing explicit services that empower software agents with context-awareness. We propose a novel context-aware exception handling mechanism and discuss some lessons learned during its integration in the MoCA infrastructure.
TranSim: Accelerating simulation of large-scale IP networks through preserving network invariants
Authors: Hwangnam Kim, Jennifer C. Hou, Hyuk Lim
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

In this paper, we propose a fast simulation framework, TranSim, that expedites simulation by reducing the rate of generating packet-events. In the framework, we transform an IP network into an alternate network that generates a smaller number of packet-events, conduct simulation in the ''transformed'' network, and extrapolate simulation results for the original network from those obtained in the ''transformed'' network. We formally prove that, as long as the network invariant - the bandwidth-delay product - is preserved, the network dynamics, such as the queue dynamics and the packet dropping probability at each link, and TCP dynamics, such as the congestion window, RTTs, and rate dynamics, are also preserved in the course of network transformation. We implement TranSim in ns-2, and carry out a simulation study to evaluate it against packet-level simulation, with respect to the capability of capturing transient, packet-level network dynamics, the reduction in the execution time and memory usage, and the discrepancy in the network throughput. The simulation results indicate maximally two orders of magnitude improvement in the execution time, and the performance improvement becomes more prominent as the network size increases (in terms of the number of nodes, the number of flows, the complexity of topology, and link capacity) or as the degree of downsizing increases. The memory usage incurred in TranSim is comparable to that in packet-level simulation. The error discrepancy between TranSim and packet-level simulation, on the other hand, is between 1% and 10% in a wide variety of network topologies, inclusive of randomly generated topologies, traffic loads with different AQM strategies, different combination of operating systems and hardware systems.
Effect of Korteweg Stress in Miscible Liquid Two-Layer Flow in a Microfluidic Device
Authors: Y. Sugii, K. Okamoto, A. Hibara, M. Tokeshi, T. Kitamori
Venue: Journal of Visualization (2005)

Miscible liquid two-layer flow in a Y-shaped microfluidic device, which consists of microchannels with 120 &mu;m in width and 35 &mu;m in depth, is investigated by particle image velocimetry (PIV) to clarify the flow characteristics at fluid interfaces. The obtained velocities with a spatial resolution of 5.9 &times; 1.5 &mu;m$^2$ around the interface between water and ethanol indicate an imbalance in shear stress at interface. The reason of the imbalance is to be the Korteweg stress generated by interfacial tension gradient due to a concentration gradient by diffusion in a miscible two-layer flow. The stress may cause an interfacial instability and destroy a uniform mixing in two flowing fluids in the case of large concentration gradient.
Algorithms for 2-Route Cut Problems
Authors: Chandra Chekuri, Sanjeev Khanna
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

In this paper we study approximation algorithms for multi-route cut problems in undirected graphs. In these problems the goal is to find a minimum cost set of edges to be removed from a given graph such that the edge-connectivity (or node-connectivity) between certain pairs of nodes is reduced below a given threshold K. In the usual cut problems the edge connectivity is required to be reduced below 1 (i.e. disconnected). We consider the case of K = 2 and obtain poly-logarithmic approximation algorithms for fundamental cut problems including single-source, multiway-cut, multicut, and sparsest cut. These cut problems are dual to multi-route flows that are of interest in fault-tolerant networks flows. Our results show that the flow-cut gap between 2-route cuts and 2-route flows is poly-logarithmic in undirected graphs with arbitrary capacities. 2-route cuts are also closely related to well-studied feedback problems and we obtain results on some new variants. Multi-route cuts pose interesting algorithmic challenges. The new techniques developed here are of independent technical interest, and may have applications to other cut and partitioning problems.
PR-MAC: Path-Oriented Real-Time MAC Protocol for Wireless Sensor Network
Authors: Jianrong Chen, Peidong Zhu, Zhichang Qi
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

This paper proposes a Path-oriented Real-time Medium Access Control (PR-MAC) protocol for sensor networks to guarantee the bounded delay of data transmission. PR-MAC removes sleep delay with a Bidirectional Pipelining Schedule (BPS) algorithm, and reduces communication delay caused by contention with a multi-channel communication mechanism. BPS enables a node to wake twice during a work cycle so as to support bidirectional data transmission. In either direction, the nodes along a path wake up sequentially. The multi-channel mechanism allocates a special channel for each communication path so that multiple simultaneous events will not interfere with one another. The data delay and energy consumption of PR-MAC is compared with those of S-MAC and DMAC. We implement the prototype of PR-MAC on the ns-2 simulator. Experiments showed PR-MAC performs better than S-MAC in reducing the transmission delay of both data and control message.
Application of Genetic Algorithms to the Genetic Regulation Problem
Authors: Maria Fernanda Wanderley, João C. Silva, Carlos Cristiano Borges, Ana Tereza Vasconcelos
Venue: Proceedings of the 3rd Brazilian symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology (2008)

Gene expression is the process of decoding the information in a DNA sequence into a protein. In this process, an enzyme called RNA-polymerase transcribes DNA into messenger-RNA, which is translated into protein. The determinant factors to decide which protein belongs to each cell and how much of it will be produced are the concentration of mRNA, and the frequency mRNA is translated. Operators and regulators, called transcription factors, control the transcription process. The gene regulation network consists of determining how and which transcription factors are positioned in some DNA sequence. In this work, we explore the ability of genetic algorithms to search in complex spaces to find predictions of possible units of genetic information. We propose four approaches to solve this problem, trying to identify the pertinent set of parameters to be used. We use E. coli sigma 70 promoters as a study of case.
Extraction of Approximate Independent Components from Large Natural Scenes
Authors: Yoshitatsu Matsuda, Kazunori Yamaguchi
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Linear multilayer ICA (LMICA) is an approximate algorithm for independent component analysis (ICA). In LMICA, approximate independent components are efficiently estimated by optimizing only highly-dependent pairs of signals. Recently, a new method named "recursive multidimensional scaling (recursive MDS)" has been proposed for the selection of pairs of highly-dependent signals. In recursive MDS, signals are sorted by one-dimensional MDS at first. Then, the sorted signals are divided into two sections and each of them is sorted by MDS recursively. Because recursive MDS is based on adaptive PCA, it does not need the stepsize control and its global optimality is guaranteed. In this paper, the LMICA algorithm with recursive MDS is applied to large natural scenes. Then, the extracted independent components of large scenes are compared with those of small scenes in the four statistics: the positions, the orientations, the lengths, and the length to width ratios of the generated edge detectors. While there are no distinct differences in the positions and the orientations, the lengths and the length to width ratios of the components from large scenes are greater than those from small ones. In other words, longer and sharper edges are extracted from large natural scenes.
Development of an Agreement Metric Based Upon the RAND Index for the Evaluation of Dimensionality Reduction Techniques, with Applications to Mapping Customer Data
Authors: Stephen France, Douglas Carroll
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

We develop a metric ¿, based upon the RAND index, for the comparison and evaluation of dimensionality reduction techniques. This metric is designed to test the preservation of neighborhood structure in derived lower dimensional configurations. We use a customer information data set to show how ¿ can be used to compare dimensionality reduction methods, tune method parameters, and choose solutions when methods have a local optimum problem. We show that ¿ is highly negatively correlated with an alienation coefficient K that is designed to test the recovery of relative distances. In general a method with a good value of ¿ also has a good value of K. However the monotonic regression used by Nonmetric MDS produces solutions with good values of ¿, but poor values of K.
Automatic detection of dust devils and clouds on Mars
Authors: Andres Castano, Alex Fukunaga, Jeffrey Biesiadecki, Lynn Neakrase, Patrick Whelley, Ronald Greeley, Mark Lemmon, Rebecca Castano, Steve Chien
Venue: Machine Vision and Applications (2008)

The acquisition of science data in space applications is shifting from teleoperated data collection to an automated onboard analysis, resulting in improved data quality, as well as improved usage of limited resources such as onboard memory, CPU, and communications bandwidth. Science instruments onboard a modern deep-space spacecraft can acquire much more data that can be downloaded to Earth, given the limited communication bandwidth. Onboard data analysis offers a means of compressing the huge amounts of data collected and downloading only the most valuable subset of the collected data. In this paper, we describe algorithms for detecting dust devils and clouds onboard Mars rovers, and summarize the results. These algorithms achieve the accuracy required by planetary scientists, as well as the runtime, CPU, memory, and bandwidth constraints set by the engineering mission parameters. The detectors have been uploaded to the Mars Exploration Rovers, and currently are operational. These detectors are the first onboard science analysis processes on Mars.
Quantum Separation of Local Search and Fixed Point Computation
Authors: Xi Chen, Xiaoming Sun, Shang-Hua Teng
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

We give a lower bound of ¿ (n (d ¿ 1)/2) on the quantum query complexity for finding a fixed point of a discrete Brouwer function over grid [n] d . Our lower bound is nearly tight, as Grover Search can be used to find a fixed point with O(n d/2) quantum queries. Our result establishes a nearly tight bound for the computation of d-dimensional approximate Brouwer fixed points defined by Scarf and by Hirsch, Papadimitriou, and Vavasis. It can be extended to the quantum model for Sperner's Lemma in any dimensions: The quantum query complexity of finding a panchromatic cell in a Sperner coloring of a triangulation of a d-dimensional simplex with n d cells is ¿(n (d ¿ 1)/2). For d = 2, this result improves the bound of ¿(n 1/4) of Friedl, Ivanyos, Santha, and Verhoeven.More significantly, our result provides a quantum separation of local search and fixed point computation over [n] d , for d ¿ 4. Aaronson's local search algorithm for grid [n] d , using Aldous Sampling and Grover Search, makes O (n d/3) quantum queries. Thus, the quantum query model over [n] d for d ¿ 4 strictly separates these two fundamental search problems.
Improvement Techniques for the EM-Based Neural Network Approach in RF Components Modeling
Authors: Liu Tao, Zhang Wenjun, Ma Jun, Yu Zhiping
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Electromagnetic (EM)---based neural network (NN) approaches have recently gained recognition as unconventional and useful methods for radio frequency (RF) components modeling. In this paper, several improvement techniques including a new data preprocessing technique and an improved training algorithm are presented. Comprehensive cases are compared in this paper. The experimental results indicate that with these techniques, the modified model has better performance.
Human Action Recognition Using a Modified Convolutional Neural Network
Authors: Ho-Joon Kim, Joseph S. Lee, Hyun-Seung Yang
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

In this paper, a human action recognition method using a hybrid neural network is presented. The method consists of three stages: preprocessing, feature extraction, and pattern classification. For feature extraction, we propose a modified convolutional neural network (CNN) which has a three-dimensional receptive field. The CNN generates a set of feature maps from the action descriptors which are derived from a spatiotemporal volume. A weighted fuzzy min-max (WFMM) neural network is used for the pattern classification stage. We introduce a feature selection technique using the WFMM model to reduce the dimensionality of the feature space. Two kinds of relevance factors between features and pattern classes are defined to analyze the salient features.
Top 10 Architecture Land Mines
Authors: Thomas W. Rehkopf, Nicholas Wybolt
Venue: IT Professional (2003)

The architecture effort's effectiveness is only measurable by the degree to which it contributes to the business' success.
Recognizing low/high anger in speech for call centers
Authors: Fu-Ming Lee, Li-Hua Li, Ru-Yi Huang
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

Automatic multi-level anger recognition in speech is an important factor to enhance user satisfaction for call centers. In this research, three emotional states, namely, neutral, low anger, and high anger of acted corpora with telephone quality are specified for emotion recognition. The corpora are collected from amateur actors and, thereafter, verified by the actors themselves. The emotion recognizer is implemented by using Back-propagation Network (BPN) with acoustic features of speech examples. Due to the variation of expression methods by different person, the feature values of the training examples used are too complex to make the BPN model convergent. To overcome the problem, a codified method is developed to simplify the feature values. With the codified inputs, the BPN model and a comparative Decision Tree C5.0 give quite satisfactory test performances for anger recognition. Therefore, they can be used as a part of a decision support system for proper applications in call centers.
Deterministic Constructions of 21-Step Collisions for the SHA-2 Hash Family
Authors: Somitra Kumar Sanadhya, Palash Sarkar
Venue: Proceedings of the 11th international conference on Information Security (2008)

Recently, at FSE '08, Nikolić and Biryukov introduced a new technique for analyzing SHA-2 round function. Building on their work, but using other differential paths, we construct two different deterministic attacks against 21-step SHA-2 hash family. Since the attacks are deterministic, they are actually combinatorial constructions of collisions. There are six free words in our first construction. This gives exactly 2192 different collisions for 21-step SHA-256 and exactly 2384 different collisions for 21-step SHA-512. The second construction has five free words. The best previous result, due to Nikolić and Biryukov, for finding collisions for 21-step SHA-256 holds with probability 2¿ 19. No results on 21-step SHA-512 are previously known. Further, we provide evidence that the Nikolić-Biryukov differential path is unlikely to yield 21-step collisions for SHA-512.
Maximum Rigid Components as Means for Direction-Based Localization in Sensor Networks
Authors: Bastian Katz, Marco Gaertler, Dorothea Wagner
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

Many applications in sensor networks require positional information of the sensors. Recovering node positions is closely related to graph realization problems for geometric graphs. Here, we address the case where nodes have angular information. Whereas Bruck et al. proved that the corresponding realization problem together with unit-disk-graph-constraints is $\mathcal{NP}$-hard [2], we focus on rigid components which allow both efficient identification and fast, unique realizations. Our technique allows to identify maximum rigid components in graphs with partially known rigid components using a reduction to maximum flow problems. This approach is analyzed for the two-dimensional case, but can easily be extended to higher dimensions.
On Complexity of Two Dimensional Languages Generated by Transducers
Authors: Egor Dolzhenko, Nataša Jonoska
Venue: Proceedings of the 13th international conference on Implementation and Applications of Automata (2008)

We consider two-dimensional languages, called here 2d transducer languages, generated by iterative applications of transducers (finite state automata with output). To each transducer a two-dimensional language consisting of blocks of symbols is associated: the bottom row of a block is an input string accepted by the transducer and, by iterative application of the transducer, each row of the block is an output of the transducer on the preceding row. We observe that this class of languages is a proper subclass of recognizable picture languages containing the class of all factorial local 2d languages. By taking the average growth rate of the number of blocks in the language as a measure of its complexity, also known as the entropy of the language, we show that every entropy value of a one-dimensional regular language can be obtained as an entropy value of a 2d transducer language.
General Certificateless Encryption and Timed-Release Encryption
Authors: Sherman S. Chow, Volker Roth, Eleanor G. Rieffel
Venue: Proceedings of the 6th international conference on Security and Cryptography for Networks (2008)

While recent timed-release encryption (TRE) schemes are implicitly supported by a certificateless encryption (CLE) mechanism, the security models of CLE and TRE differ and there is no generic transformation from a CLE to a TRE. This paper gives a generalized model for CLE that fulfills the requirements of TRE. This model is secure against adversaries with adaptive trapdoor extraction capabilities, decryption capabilities for arbitrary public keys, and partial decryption capabilities. It also supports hierarchical identifiers. We propose a concrete scheme under our generalized model and prove it secure without random oracles, yielding the first strongly-secure security-mediated CLE and the first TRE in the standard model. In addition, our technique of partial decryption is different from the previous approach.
On Metamodel-Based Design of Software Metrics
Authors: Erki Eessaar
Venue: Balancing Agility and Formalism in Software Engineering: Second IFIP TC 2 Central and East European Conference on Software Engineering Techniques, CEE-SET 2007, Poznan, Poland, October 10-12, 2007, Revised Selected Papers (2008)

Metric values can be used in order to compare and evaluate software entities, find defects, and predict quality. For some programming languages there are much more known metrics than for others. It would be helpful, if one could use existing metrics in order to find candidates for new metrics. A solution is based on an observation that it is possible to specify abstract syntax of a language by using a metamodel. In the paper a metrics development method is proposed that uses metamodel-based translation. In addition, a metamodel of a language helps us to find the extent of a set of metrics in terms of that language. That allows us to evaluate the extent of the core of a language and to detect possible quality problems of a set of metrics. The paper contains examples of some candidate metrics for object-relational database design, which have been derived from existing metrics.
An Architectural Comparison of Contemporary 16-Bit Microprocessors
Authors: Hoo-min Toong, Amar Gupta
Venue: IEEE Micro (1981)

Today's microprocessors exhibit powerful computing capabilities. Their characteristic differences favor each machine for a distinct portion of the applications spectrum.