ppxscal/embedding_network huggingface dataset:
Neural Network Training Using Genetic Algorithm with a Novel Binary Encoding
Authors: Yong Liang, Kwong-Sak Leung, Zong-Ben Xu
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Genetic algorithms (GAs) are widely used in the parameter training of Neural Network (NN). In this paper, we investigate GAs based on our proposed novel genetic representation to train the parameters of NN. A splicing/decomposable (S/D) binary encoding is designed based on some theoretical guidance and existing recommendations. Our theoretical and empirical investigations reveal that the S/D binary representation is more proper than other existing binary encodings for GAs' searching. Moreover, a new genotypic distance on the S/D binary space is equivalent to the Euclidean distance on the real-valued space during GAs convergence. Therefore, GAs can reliably and predictably solve problems of bounded complexity and the methods depended on the Euclidean distance for solving different kinds of optimization problems can be directly used on the S/D binary space. This investigation demonstrates that GAs based our proposed binary representation can efficiently and effectively train the parameters of NN.
Improving the Data Delivery Latency in Sensor Networks with Controlled Mobility
Authors: Ryo Sugihara, Rajesh K. Gupta
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

Unlike traditional multihop forwarding among homogeneous static sensor nodes, use of mobile devices for data collection in wireless sensor networks has recently been gathering more attention. It is known that the use of mobility significantly reduces the energy consumption at each sensor, elongating the functional lifetime of the network, in exchange for increased data delivery latency. However, in previous work, mobility and communication capabilities are often underutilized, resulting in suboptimal solutions incurring unnecessarily large latency. In this paper, we focus on the problem of finding an optimal path of a mobile device, which we call "data mule," to achieve the smallest data delivery latency in the case of minimum energy consumption at each sensor, i.e., each sensor only sends its data directly to the data mule. We formally define the path selection problem and show the problem is $\mathcal{NP}$-hard. Then we present an approximation algorithm and analyze its approximation factor. Numerical experiments demonstrate that our approximation algorithm successfully finds the paths that result in 10%-50% shorter latency compared to previously proposed methods, suggesting that controlled mobility can be exploited much more effectively.
Admissible Fuzzy Controller in L2 Space
Authors: Takashi Mitsuishi, Yasunari Shidama
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

This article presents a mathematical framework for studying the existence of optimal feedback control based on IF-THEN fuzzy rules through approximate reasoning, and introduces the notion of an admissible fuzzy controller. The framework consists of two propositions: To guarantee the convergence of optimal solution, a set of fuzzy membership functions (admissible fuzzy controller) which are selected out of L 2 space is convex and compact metrizable for the weak topology. And assuming approximate reasoning to be a functional on the set of membership functions, its continuity is proved. Then, we show the existence of a fuzzy controller which minimize (maximize) the integral performance function of the nonlinear feedback system.
Preliminary Evaluation of a Phase Contrast Imaging with Digital Mammography
Authors: Satoru Matsuo, Hiroshi Fujita, Junji Morishita, Tetsuro Katafuchi, Chika Honda, Junko Sugiyama
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

X-ray beams irradiated from an x-ray tube with a point source or a sufficiently small focal spot produce edge-enhanced images in the boundary of an object due to the effect of phase shift of x-rays. This technique is called phase contrast imaging. A digital phase contrast imaging system based on a photostimulable phosphor plate (imaging plate) designed for mammography has been developed for clinical use recently and now commercially available. In this study, the digital phase contrast images of an acrylic plate and plant seeds were acquired without any increase of incident dose to detector when compared to conventional contact digital imaging. Improvement of image edge sharpness was evaluated in terms of spatial edge response and spectral analysis of the images. In addition, the improvement of the sharpness of the image was also evaluated in clinical mammograms. Our results indicated that higher image sharpness in the boundary of the object was observed. The power spectrum of the digital phase contrast image was found to be higher than that of the digital contact image at wide spatial frequency region. In conclusion, the commercially available phase contrast imaging system can provide breast images with details that are not available in conventional mammograms. The digital phase contrast imaging would be useful to detect diseases, especially microcalcifications, in mammograms without any increase of exposure dose.
Geodesy on label images, and applications to video sequence processing
Authors: Christian Ronse, Vincent Agnus
Venue: Journal of Visual Communication and Image Representation (2008)

Morphological operators based on the numerical ordering of grey-levels are used to filter regional minima and maxima in images. It is argued that label images constitute an appropriate framework for morphological filtering of regions which are neither minima nor maxima. Following a previous paper where we introduced morphological operations on label images [C. Ronse, V. Agnus, Morphology on label images: flat-type operators and connections, Journal of Mathematical Imaging and Vision 22 (2/3) (2005) 283-307], we study geodesic dilation (or erosion) and reconstruction. Since the lattice of label images is not distributive, some strange results may happen, so the standard definition of geodesic dilation and reconstruction must be modified in order to be effective; standard properties of geodesic operations are preserved only if we make some restrictions on the labels present in the mask or marker image. We give the relation between geodesic reconstruction and the flat zone connection on label images. We illustrate the theory with an application of morphology and geodesy on label images, to the segmentation of moving objects in video sequences.
Introducing probabilistic radio propagation models in OMNeT++ mobility framework and cross validation check with NS-2
Authors: A. Kuntz, F. Schmidt-Eisenlohr, O. Graute, H. Hartenstein, M. Zitterbart
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

When performing wireless network simulations, the lack of precise channel modeling in simulator frameworks becomes a serious problem. Often deterministic models are used for packet propagation, which describe real conditions insufficiently. To close this gap we extended the OMNeT++ Mobility Framework to support probabilistic propagation models. We provide an implementation for the Log-Normal-Shadowing, Nakagami, Rayleigh and Rice wave propagation models and set up a framework that allows easy integration of additional models in future. Due to the characteristics of probabilistic radio models a fixed maximum packet propagation range encounters the problem of inaccurate simulation results as relevant events may be suppressed. On the other hand, unlimited packet propagation, which guarantees for correct simulation runs, causes unnecessary simulation overhead. In this work we present an approach to limit the event delivery to the area where the probability that the event is relevant to the simulation exceeds an adjustable threshold. In order to validate our extensions we successfully performed a detailed crosscheck with the network simulator NS-2 and run a performance evaluation and comparison.
Maximum Finding in the Symmetric Radio Networks with Collision Detection
Authors: František Galčík, Gabriel Semanišin
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

We consider a problem of computing the maximal value associated to the nodes of a network in the model of unknown symmetric radio network with availability of collision detection. We assume that the nodes have no initial knowledge about the network topology, number of nodes and even they have no identifiers. The network contains one distinguished node, called initiator, that starts the process of computing. We design a series of algorithms that result into an asymptotically optimal deterministic algorithm completing the task in ¿(ecc + logMax) rounds, where ecc is the eccentricity of the initiator and Max is the maximal value among the integer values associated to the nodes. Some other utilisations of the developed algorithm are presented as well.
A Method for Reading a Resistor by Image Processing Techniques
Authors: Yoshihiro Mitani, Yuuki Sugimura, Yoshihiko Hamamoto
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

The resistance of a resistor is defined by colored lines printed on the resistor's body. Normally, people read it by sight. Though, if a computer performs this instead, we can reduce the costs. In this paper, we propose a method for reading this resistance by image processing techniques. We extract colors from a real resistor's picture, and classify it by its colors. The experimental results show the effectiveness of the proposed method.
Towards Lightweight LMS 2.0: A Blog-Based Approach to Online Assessment
Authors: Vladimir Tomberg, Mart Laanpere
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

Blogs have not been designed for online teaching and learning, yet they have recently become a "must try" component of learning environment in academic circles. This paper focuses on one of the challenges of blog-based e-learning: implementation of feedback and assessment workflows in distributed e-learning landscape. Some most typical assessment-related workflows are described and a prototype of an add-on module for an open-source blogging tool Wordpress is demonstrated.
Using global data flow analysis on bytecode to aid worst case execution time analysis for real-time Java programs
Authors: James J. Hunt, Isabel Tonin, Fridtjof B. Siebert
Venue: Proceedings of the 6th international workshop on Java technologies for real-time and embedded systems (2008)

Though real-time Java offers significant advantages over other programming languages for safe programming, the analysis of worst case execution of real-time Java programs is considerably more difficult. The extra complexity can be addressed using a minimal set of parameterized annotations and data flow analysis to provide a standard worst case execution time analysis tool with the additional information necessary to determine the worst case execution time analysis of real-time Java programms. This methodology has the advantage over existing methods in that it is equally applicable to general purpose library code as to application specific implementation code.
Maximum Connected Domatic Partition of Directed Path Graphs with Single Junction
Authors: Masaya Mito, Satoshi Fujita
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

In this paper, we consider the problem of finding a maximum connected domatic partition of a given graph. We propose a polynomial time algorithm for solving the problem for a subclass of directed path graphs which is known as a class of intersection graphs modeled by a set of directed paths on a directed tree. More specifically, we restrict the class of directed path graphs in such a way that the underlying directed tree has at most one node to have several incoming arcs.
Recasting Constraint Automata into Büchi Automata
Authors: Mohammad Izadi, Marcello M. Bonsangue
Venue: Proceedings of the 5th international colloquium on Theoretical Aspects of Computing (2008)

Constraint automata have been proposed as the operational semantics of Reo, a glue-code language for the exogenous composition and orchestration of components in a software system. In this paper we recast the theory of constraint automata into that of Büchi automata on infinite strings of records. We use records to express simultaneity constraints of I/O operations and show that every constraint automaton can be expressed as a Büchi automaton on an appropriate alphabet of records. Further, we give examples of component compositions that are expressible as Büchi automata but not as constraint automata. Finally, we show that the join composition operator for constraint automata and its counterpart for Büchi automata of records can be expressed as two basic operations on Büchi automata: alphabet extension and product.
The Algorithm Concept --- Tool for Historiographic Interpretation or Red Herring?
Authors: Jens Høyrup
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

With starting point in Donald Knuth's paper "Ancient Babylonian Algorithms", and using the algebraic reading of pre-Modern mathematical texts as a parallel, the paper discusses the relevance of the algorithm concept, on one hand as an analytical tool for the understanding and comparison of mathematical procedures, on the other as a possible key to how pre-Modern reckoners thought their mathematics and to how they thought about it.
A Hardware-Software Design Framework for Distributed Cellular Computing
Authors: Pierre-André Mudry, Julien Ruffin, Michel Ganguin, Gianluca Tempesti
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

In this article, we describe a novel hardware-software design framework for prototyping cellular architectures in hardware. Based on an extensible platform of about 200 FPGAs, configured as a networked structure of processors, the hardware part of this computing framework is backed by an extensible library of software components that provides primitives for efficient inter-processor communication and distributed computation. This dual software---hardware approach allows a very quick exploration of different ways to solve computational problems using bio-inspired techniques. To demonstrate the validity of the method, we present an example of how a traditional parallel system such as a cellular automaton can be modeled and run with this perspective. In addition, we also show that the flexibility of our approach allows not only cellular automata but any computation to be easily implemented on a cellular substrate.
Linear Programming Relax-PSO Hybrid Bound Algorithm for a Class of Nonlinear Integer Programming Problems
Authors: Yuelin Gao, Chengxian Xu, Jimin Li
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

The paper researches a class of nonlinear integer programming problems the objective function of which is the sum of the products of some nonnegative linear functions in the given rectangle and the constraint functions of which are all linear as well as strategy variables of which are all integer ones. We give a linear programming relax-PSO hybrid bound algorithm for solving the problem. The lower bound of the optimal value of the problem is determined by solving a linear programming relax which is obtained through equally converting the objective function into the exponential-logarithmic composite function and linearly lower approximating each exponential function and each logarithmic function over the rectangles. The upper bound of the optimal value and the feasible solution of it are found and renewed with particle swarm optimization (PSO). It is shown by the numerical results that the linear programming relax-PSO hybrid bound algorithm is better than the branch-and-bound algorithm in the computational scale and the computational time and the computational precision and overcomes the convergent difficulty of PSO.
Longest Common Separable Pattern Among Permutations
Authors: Mathilde Bouvel, Dominique Rossin, Stéphane Vialette
Venue: Proceedings of the 18th annual symposium on Combinatorial Pattern Matching (2007)

In this paper, we study the problem of finding the longest common separable pattern among several permutations. We first give a polynomial-time algorithm when the number of input permutations is fixed and next show that the problem is NP---hardfor an arbitrary number of input permutations even if these permutations are separable.On the other hand, we show that the NP---hardproblem of finding the longest common pattern between two permutations cannot be approximated better than within a ratio of (where is the size of an optimal solution) when taking common patterns belonging to pattern-avoiding permutation classes.
Adaptive integration in the visual cortex by depressing recurrent cortical circuits
Authors: Mark C. W. van Rossum, Matthijs A. A. van der Meer, Dengke Xiao, Mike W. Oram
Venue: Neural Computation (2008)

Neurons in the visual cortex receive a large amount of input from recurrent connections, yet the functional role of these connections remains unclear. Here we explore networks with strong recurrence in a computational model and show that short-term depression of the synapses in the recurrent loops implements an adaptive filter. This allows the visual system to respond reliably to deteriorated stimuli yet quickly to high-quality stimuli. For low-contrast stimuli, the model predicts long response latencies, whereas latencies are short for high-contrast stimuli. This is consistent with physiological data showing that in higher visual areas, latencies can increase more than 100 ms at low contrast compared to high contrast. Moreover, when presented with briefly flashed stimuli, the model predicts stereotypical responses that outlast the stimulus, again consistent with physiological findings. The adaptive properties of the model suggest that the abundant recurrent connections found in visual cortex serve to adapt the network's time constant in accordance with the stimulus and normalizes neuronal signals such that processing is as fast as possible while maintaining reliability.
Multiresolution analyses originated from nonstationary subdivision schemes
Authors: Laura Gori, Francesca Pitolli
Venue: Journal of Computational and Applied Mathematics (2008)

We analyze the properties of a new class of totally positive refinable functions obtained from nonstationary subdivision schemes. We show that the corresponding system of the integer translates is linearly independent, satisfies a Whitney-Schoenberg condition, reproduces polynomials up to a certain degree and generates a multiresolution analysis. Finally, pre-wavelets and bases on the interval are constructed.
Characterization of Projection Ordering in Iterative Reconstruction Methods for Breast Tomosynthesis
Authors: Gang Wu, James Mainprize, Martin Yaffe
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

The order in which the projection views are selected in the reconstruction of tomosynthesis by iterative algorithms, such as algebraic reconstruction technique (ART) and maximum likelihood (ML), has a strong effect on rate of convergence, accuracy and the edge-blurring artifacts in the reconstructed image. In this work, we compared several ordering schemes and characterized the image quality and the formation of out-of-plane artifacts. A new projection sequence is presented, which produces more accurate reconstructions with reduced artifact intensity compared to sequential ordering. The new ordering achieved more than a 48% improvement in image quality index for a uniform background phantom after two iterations.
An adaptive cut-off for task parallelism
Authors: Alejandro Duran, Julita Corbalán, Eduard Ayguadé
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

In task parallel languages, an important factor for achieving a good performance is the use of a cut-off technique to reduce the number of tasks created. Using a cut-off to avoid an excessive number of tasks helps the runtime system to reduce the total overhead associated with task creation, particularlt if the tasks are fine grain. Unfortunately, the best cut-off technique its usually dependent on the application structure or even the input data of the application. We propose a new cut-off technique that, using information from the application collected at runtime, decides which tasks should be pruned to improve the performance of the application. This technique does not rely on the programmer to determine the cut-off technique that is best suited for the application. We have implemented this cut-off in the context of the new OpenMP tasking model. Our evaluation, with a variety of applications, shows that our adaptive cut-off is able to make good decisions and most of the time matches the optimal cut-off that could be set by hand by a programmer.
Adaptive Distributed Time-Slot Based Scheduling for Fairness in Multi-Hop Wireless Networks
Authors: Ananth Rao, Ion Stoica
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Recent research indicates that multi-hop wireless networks can suffer from extreme imbalances in the throughput achieved by simultaneous competing flows. We address this problem by designing a practical distributed algorithm to compute a time-slot based schedule that provides end-to-end Max-Min fairness. Our system uses randomized priorities based on local weights to arbitrate access between nodes that directly compete with each other (we call this Weighted Slot Allocation or WSA). The local weights are in turn computed by a higher layer called End-to-end Fairness using Local Weights (EFLoW). EFLoW implements an additive-increase multiplicative-decrease (AIMD) algorithm that can automatically adapt to changes in traffic demands and network conditions. In each iteration, EFLoW only uses state obtained from within a given node's contention region. We have implemented WSA and EFLoW in both a simulator and a real system by using the Overlay MAC Layer (OML). Unlike previous work on end-to-end fairness, our approach does not use a centralized coordinator and works for traffic patterns with any number of sources and sinks. Also, since we compute both the fair allocation and a schedule to achieve it, we do not make any assumptions about the efficiency of carrier-sense (CS) based MACs - this is very important in the light of recent work which shows that current CS-based MACs can be very unfair even when all nodes are limited to sending at their fair rate. Our results show that WSA and EFLoW can prevent starvation of flows and improve fairness without sacrificing efficiency for a wide variety of traffic patterns.