ppxscal/embedding_network huggingface dataset:
Algorithms for Inner Magic and Inner Antimagic Labelings of Some Planar Graphs
Authors: Auparajita Krishnaa, Manohar Singh Dulawat
Venue: Informatica (2006)

In this work labeling of planar graphs is taken up which involves labeling the p vertices, the q edges and the f internal faces such that the weights of the faces form an arithmetic progression with common difference d. If d=0, then the planar graph is said to have an Inner Magic labeling; and if d&ne;0, then it is Inner Antimagic labeling. Some new kinds of graphs have been developed which have been derived from Wheels by adding vertices in a certain way and it is proposed to give new names to these graphs namely Flower-1 and Flower-2. This paper presents the algorithms to obtain the Inner Magic and Inner Antimagic labeling for Wheels and the Inner Antimagic labeling for Flower-1 and Flower-2. The results thus found show much regularity in the labelings obtained.
Obstacle Avoidance Path Planning for Mobile Robot Based on Ant-Q Reinforcement Learning Algorithm
Authors: Ngo Anh Vien, Nguyen Hoang Viet, Seunggwan Lee, Taechoong Chung
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Path planning is an important task in mobile robot control. When the robot must move rapidly from any arbitrary start positions to any target positions in environment, a proper path must avoid both static obstacles and moving obstacles of arbitrary shape. In this paper, an obstacle avoidance path planning approach for mobile robots is proposed by using Ant-Q algorithm. Ant-Q is an algorithm in the family of ant colony based methods that are distributed algorithms for combinatorial optimization problems based on the metaphor of ant colonies. In the simulation, we experimentally investigate the sensitivity of the Ant-Q algorithm to its three methods of delayed reinforcement updating and we compare it with the results obtained by other heuristic approaches based on genetic algorithm or traditional ant colony system. At last, we will show very good results obtained by applying Ant-Q to bigger problem: Ant-Q find very good path at higher convergence rate.
Helmut Hoelzer's Fully Electronic Analog Computer
Authors: James E. Tomayko
Venue: IEEE Annals of the History of Computing (1985)

A fully electronic general-purpose analog computer was designed by Helmut Hoelzer, a German electrical engineer and remote-controlled guidance specialist. He and an assistant built the device in 1941 in Peenemunde, Germany, where they were working as part of Wernher von Braun's long-range rocket development team. The computer was based on an electronic integrator and differentiator conceived by Hoelzer in 1935 and first applied to the guidance system of the A-4 rocket. This computer is significant in the history not only of analog computation but also of the formulation of simulation techniques. It contributed to a system for rocket development that resulted in vehicles capable of reaching the moon. 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
Computation of Semantic Models Directed by Categorial Expressions
Authors: Xiaoli Xu, Tao Zhu
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

Around the core issue of how to construct the literal meaning of natural language, we provide the theory of computation of categorial expressions directed by phrasal structures. This theory uses hierarchial method to describe and interpret language phenomena. We formalize a categorial expression as a directed acyclic graph and define the reduction and unification calculus of categorial expressions.
Using interactive multiobjective methods to solve DEA problems with value judgements
Authors: Brandon Y. H. Wong, Mariano Luque, Jian-Bo Yang
Venue: Computers and Operations Research (2009)

Data envelopment analysis (DEA) is a performance measurement tool that was initially developed without consideration of the decision maker (DM)'s preference structures. Ever since, there has been a wide literature incorporating DEA with value judgements such as the goal and target setting models. However, most of these models require prior judgements on target or weight setting. This paper will establish an equivalence model between DEA and multiple objective linear programming (MOLP) and show how a DEA problem can be solved interactively without any prior judgements by transforming it into an MOLP formulation. Various interactive multiobjective models would be used to solve DEA problems with the aid of PROMOIN, an interactive multiobjective programming software tool. The DM can then search along the efficient frontier to locate the most preferred solution where resource allocation and target levels based on the DM's value judgements can be set. An application on the efficiency analysis of retail banks in the UK is examined. Comparisons of the results among the interactive MOLP methods are investigated and recommendations on which method may best fit the data set and the DM's preferences will be made.
Engineering large-scale distributed auctions
Authors: Peter Gradwell, Michel Oey, Reinier Timmer, Frances Brazier, Julian Padget
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

The functional characteristics of market-based solutions are typically best observed through the medium of simulation, data-gathering and subsequent visualization. We previously developed a simulation of multiple distributed auctions to handle resource allocation (in fact, bundles of unspecified goods) and in this paper we want to deploy an equivalent system as a distributed application. There are two notable problems with the simulation-first, application-second approach: (i) the simulation cannot reasonably take account of network effects, and (ii) how to recreate in a distributed application the characteristics demonstrated by the mechanism in the simulation. We describe: (i) the refactorings employed in the process of transforming a uni-processor lock-step simulation into a multiprocessor asynchronous system, (ii) some preliminary performance indicators, and (iii) some reflections on our experience which may be useful in building MAS in general.
SNMP parameters for 802.11 network performance measuring
Authors: Waldeck Ribeiro Torres, Maria Luiza D'Almeida Sanchez
Venue: Proceedings of the 2008 Ambi-Sys workshop on Software Organisation and MonIToring of Ambient Systems (2008)

Reliability and stability are essential conditions for proper operation of any communication system, it is more critical if we talk about wireless networks. Some applications are not fault tolerant for data loss or even synchronization issues; it means that administrators should care not only about application itself but with physical layer as well. By tracking performance and status using open source and standardized protocol is possible to correct or predict possible operational problems at network. In this paper we describe relevant 802.11 SNMP MIB set of parameters with suggestions of optimum values to each one. We also describe some data correlation possibilities, measurement scenarios and cases studies to be used as reference for wireless network administration. The proposal is to correlate gathered data from wireless nodes with environmental information.
Optimization of Fuzzy Model Driven to IG and HFC-Based GAs
Authors: Jeoung-Nae Choi, Sung-Kwun Oh, Hyung-Soo Hwang
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

The paper concerns the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) and information data granulation. HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. The granulation is realized with the aid of the Hard C-means clustering (HCM). The concept of information granulation was applied to the fuzzy model in order to enhance the abilities of structural optimization. By doing that, we divide the input space to form the premise part of the fuzzy rules and the consequence part of each fuzzy rule is newly organized based on center points of data group extracted by the HCM clustering. It concerns the fuzzy model-related parameters such as the number of input variables, a collection of specific subset of input variables, the number of membership functions, and the polynomial type of the consequence part of fuzzy rules. In the hybrid optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.
An Approach for Enriching Information for Supporting Collaborative e-Work
Authors: Obinna Anya, Atulya Nagar, Hissam Tawfik
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

As a result of the high level of knowledge required in collaborative e-Work as well as its changing work contexts, e-Work support systems need to provide not only information in the form of documents and articles, but also expert-level explanations in the form of supporting literature and references to theories and related cases, to justify retrieved information and offer cognitive support to e-Work. In this paper, we present a novel approach for enriching information for supporting collaborative e-Work, which combines latent semantic analysis, domain task modelling and conceptual learning. We illustrate the potential of our approach using our e-Workbench system. e-Workbench is a prototype system for adaptive collaborative e-Work.
Model Checking Knowledge and Linear Time: PSPACE Cases
Authors: Kai Engelhardt, Peter Gammie, Ron Meyden
Venue: Proceedings of the international symposium on Logical Foundations of Computer Science (2007)

We present a general algorithm scheme for model checking logics of knowledge, common knowledge and linear time, based on bisimulations to a class of structures that capture the way that agents update their knowledge. We show that the scheme leads to PSPACE implementations of model checking the logic of knowledge and linear time in several special cases: perfect recall systems with a single agent or in which all communication is by synchronous broadcast, and systems in which knowledge is interpreted using either the agents' current observation only or its current observation and clock value. In all these results, common knowledge operators may be included in the language. Matching lower bounds are provided, and it is shown that although the complexity bound matches the PSPACE complexity of the linear time temporal logic LTL, as a function of the model size the problems considered have a higher complexity than LTL.
Compactness Properties for Stable Semantics of Logic Programs
Authors: Victor W. Marek, Jeffrey B. Remmel
Venue: Proceedings of the international symposium on Logical Foundations of Computer Science (2007)

Logic programming with stable logic semantics (SLP) is a logical formalism that assigns to sets of clauses in the language admitting negations in the bodies a special kind of models, called stable models. This formalism does not have the compactness property. We show a number of conditions that entail a form of compactness for SLP.
Reoptimization of the Metric Deadline TSP
Authors: Hans-Joachim Böckenhauer, Dennis Komm
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

The reoptimization version of an optimization problem deals with the following scenario: Given an input instance together with an optimal solution for it, the objective is to find a high-quality solution for a locally modified instance.In this paper, we investigate several reoptimization variants of the traveling salesman problem with deadlines in metric graphs (Δ -DlTSP). The objective in the Δ -DlTSP is to find a minimum-cost Hamiltonian cycle in a complete undirected graph with a metric edge cost function which visits some of its vertices before some prespecified deadlines. As types of local modifications, we consider insertions and deletions of a vertex as well as of a deadline.We prove the hardness of all of these reoptimization variants and give lower and upper bounds on the achievable approximation ratio which are tight in most cases.
Cooperative Security Schemes for Mobile Ad-Hoc Networks
Authors: P. Caballero-Gil, C. Hernández-Goya
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

The existence of selfish nodes, who do not cooperate in routing and forwarding, is one of the most critical problems for the applicability of Mobile Ad-hoc NETworks (MANETs). In this paper we propose several novel currency-based methods for stimulating cooperation among nodes of a MANET. In particular, the proposed protocols allow improving different aspects of previous schemes based on virtual currency thanks to the incorporation of the concept of credit that will allow broke nodes to use the network while they have not a selfish behaviour. A complete analysis of simulations leads to several conclusions that establish the improvement of the proposal with respect to previous schemes.
A real-time intrusion prevention system for commercial enterprise databases and file systems
Authors: Ulf T. Mattsson
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

Modern intrusion detection systems are comprised of three basically different approaches, host based, network based, and a third relatively recent addition called procedural based detection. The first two have been extremely popular in the commercial market for a number of years now because they are relatively simple to use, understand and maintain. However, they fall prey to a number of shortcomings such as scaling with increased traffic requirements, use of complex and false positive prone signature databases, and their inability to detect novel intrusive attempts. This intrusion detection system interacts with the access control system to deny further access when detection occurs and represent a practical implementation addressing these and other concerns. This paper presents an overview of our work in creating a practical database intrusion detection system. Based on many years of Database Security Research, the proposed solution detects a wide range of specific and general forms of misuse, provides detailed reports, and has a low false-alarm rate. Traditional commercial implementations of database security mechanisms are very limited in defending successful data attacks. Authorized but malicious transactions can make a database useless by impairing its integrity and availability. The proposed solution offers the ability to detect misuse and subversion through the direct monitoring of database operations inside the database host, providing an important complement to host-based and network-based surveillance. Suites of the proposed solution may be deployed throughout a network, and their alarms managed, correlated, and acted on by remote or local subscribing security services, thus helping to address issues of decentralized management.
Distributed Private Data Analysis: Simultaneously Solving How and What
Authors: Amos Beimel, Kobbi Nissim, Eran Omri
Venue: Proceedings of the 28th Annual conference on Cryptology: Advances in Cryptology (2008)

We examine the combination of two directions in the field of privacy concerning computations over distributed private inputs --- secure function evaluation (SFE) and differential privacy. While in both the goal is to privately evaluate some function of the individual inputs, the privacy requirements are significantly different. The general feasibility results for SFE suggest a natural paradigm for implementing differentially private analyses distributively: First choose what to compute, i.e., a differentially private analysis; Then decide how to compute it, i.e., construct an SFE protocol for this analysis. We initiate an examination whether there are advantages to a paradigm where both decisions are made simultaneously. In particular, we investigate under which accuracy requirements it is beneficial to adapt this paradigm for computing a collection of functions including Binary Sum, Gap Threshold, and Approximate Median queries. Our results yield new separations between the local and global models of computations for private data analysis.
Neuro-inspired Speech Recognition with Recurrent Spiking Neurons
Authors: Arfan Ghani, T. Martin Mcginnity, Liam P. Maguire, Jim Harkin
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

This paper investigates the potential of recurrent spiking neurons for classification problems. It presents a hybrid approach based on the paradigm of Reservoir Computing. The practical applications based on recurrent spiking neurons are limited due to their non-trivial learning algorithms. In the paradigm of Reservoir Computing, instead of training the whole recurrent network only the output layer (known as readout neurons) are trained. These recurrent neural networks are termed as microcircuits which are viewed as basic computational units in cortical computation. These microcircuits are connected as columns which are linked with other neighboring columns in cortical areas. These columns read out information from each other and can serve both as reservoir and readout. The design space for this paradigm is split into three domains; front end, reservoir, and back end. This work contributes to the identification of suitable front and back end processing techniques along with stable and compact reservoir dynamics, which provides a reliable framework for classification related problems.
Behaviour of Texture Features in a CBIR System
Authors: César Reyes, Maria Luisa Durán, Teresa Alonso, Pablo G. Rodríguez, Andrés Caro
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Searching and processing in databases of general and non-specific images are highly subjective. The process of texture feature extraction from images produces results of highly theoretical and mathematical character that have little to do with human perception. We present a method to select from low-level texture features, statistics and numerical groupings and to transform them into other high-level features, with visual meaning. We also aim to facilitate their use within CBIR systems. The detailed study of the composition and behaviour of the texture characteristics has enabled us to abstract and use them in an automated manner, similarly to how an observer would do.
Plenary lecture I: use of intelligent evolutionary agents in the analysis of genomic signals
Authors: Paul Dan Cristea
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

Surprising regularities in the distribution of nucleotides and pairs of nucleotides along the genomes of both prokaryotes and eukaryotes become evident when converting nucleotide sequences from symbolic to digital form. These regularities make the structure of a genome be less like that of a "plain text", which simply conveys a semantics in accordance to a grammar, and more like that of a "poem", which obeys additional structural rules that give "rhythm" and "rhyme". Direct applications of the rules satisfied by nucleotide sequences are (1) objective evaluation of sequencing process quality, (2) prediction of nucleotides sequences similarly to time series, (3) revealing of genome ancestral structure, (4) analysis of pathogen variability. Intelligent Evolutionary Agents are used to track pathogen variability, specifically to identify drug resistance mutations, without the need of the conventional lengthily and expensive phenotypic clinical studies that request pathogen culture.
Finding conserved patterns in biological sequences, networks and genomes
Authors: Sing-Hoi Sze
Venue:  (2007)

Biological patterns are widely used for identifying biologically interesting regions within macromolecules, classifying biological objects, predicting functions and studying evolution. Good pattern finding algorithms will help biologists to formulate and validate hypotheses in an attempt to obtain important insights into the complex mechanisms of living things. In this dissertation, we aim to improve and develop algorithms for five biological pattern finding problems. For the multiple sequence alignment problem, we propose an alternative formulation in which a final alignment is obtained by preserving pair-wise alignments specified by edges of a given tree. In contrast with traditional NP-hard formulations, our preserving alignment formulation can be solved in polynomial time without using a heuristic, while having very good accuracy. For the path matching problem, we take advantage of the linearity of the query path to reduce the problem to finding a longest weighted path in a directed acyclic graph. We can find k paths with top scores in a network from the query path in polynomial time. As many biological pathways are not linear, our graph matching approach allows a non-linear graph query to be given. Our graph matching formulation overcomes the common weakness of previous approaches that there is no guarantee on the quality of the results. For the gene cluster finding problem, we investigate a formulation based on constraining the overall size of a cluster and develop statistical significance estimates that allow direct comparisons of clusters of different sizes. We explore both a restricted version which requires that orthologous genes are strictly ordered within each cluster, and the unrestricted problem that allows paralogous genes within a genome and clusters that may not appear in every genome. We solve the first problem in polynomial time and develop practical exact algorithms for the second one. In the gene cluster querying problem, based on a querying strategy, we propose an efficient approach for investigating clustering of related genes across multiple genomes for a given gene cluster. By analyzing gene clustering in 400 bacterial genomes, we show that our algorithm is efficient enough to study gene clusters across hundreds of genomes.
Energy-Aware Adaptive Routing for Large-Scale Ad Hoc Networks: Protocol and Performance Analysis
Authors: Qing Zhao, Lang Tong, David Counsil
Venue: IEEE Transactions on Mobile Computing (2007)

We propose and analyze an energy-aware traffic-adaptive routing strategy for large-scale mobile ad hoc networks. Referred to as Energy-Aware GEolocation-aided Routing (EAGER), this protocol optimally blends proactive and reactive strategies for energy efficiency. Specifically, EAGER partitions the network into cells and performs intra-cell proactive routing and inter-cell reactive routing. The cell size and transmission range are optimized analytically. By adjoining cells around hot spots and hot routes in the network, EAGER is capable of handling time-varying and spatially heterogeneous traffic conditions.