ppxscal/embedding_network huggingface dataset:
Binding Number and Connected (g,f + 1)-Factors in Graphs
Authors: Jiansheng Cai, Guizhen Liu, Jianfeng Hou
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Let G be a connected graph of order n and let a,b be two integers such that 2 ≤ a ≤ b. Let g and f be two integer-valued functions defined on V(G) such that a ≤ g(x) ≤ f(x) ≤ b for every x ¿ V(G). A spanning subgraph F of G is called a (g,f + 1)-factor if g(x) ≤ d F (x) ≤ f(x) + 1 for every x ¿ V(F). For a subset X of V(G), let $N_{G}(X)=\bigcup \limits _{x\in X}N_{G}(x)$. The binding number of G is defined by $bind(G)=min\{\frac{\mid N_{G}(X) \mid}{\mid X\mid}\mid \emptyset\neq X\subset V(G), N_{G}(X)\neq V(G)\}$. In this paper, it is proved that if $bind(G)> \frac{(a+b)(n-1)}{an}$, f(V(G)) is even and $n\geq \frac{(a+b)^{2}}{a}$, then G has a connected (g,f + 1)-factor.
Clustering high dimensional data: A graph-based relaxed optimization approach
Authors: Chi-Hoon Lee, Osmar R. Zaïane, Ho-Hyun Park, Jiayuan Huang, Russell Greiner
Venue: Information Sciences: an International Journal (2008)

There is no doubt that clustering is one of the most studied data mining tasks. Nevertheless, it remains a challenging problem to solve despite the many proposed clustering approaches. Graph-based approaches solve the clustering task as a global optimization problem, while many other works are based on local methods. In this paper, we propose a novel graph-based algorithm ''GBR'' that relaxes some well-defined method even as improving the accuracy whilst keeping it simple. The primary motivation of our relaxation of the objective is to allow the reformulated objective to find well distributed cluster indicators for complicated data instances. This relaxation results in an analytical solution that avoids the approximated iterative methods that have been adopted in many other graph-based approaches. The experiments on synthetic and real data sets show that our relaxation accomplishes excellent clustering results. Our key contributions are: (1) we provide an analytical solution to solve the global clustering task as opposed to approximated iterative approaches; (2) a very simple implementation using existing optimization packages; (3) an algorithm with relatively less computation time over the number of data instances to cluster than other well defined methods in the literature.
Coordination in ambiguity: coordinated active localization for multiple robots
Authors: Shivudu Bhuvanagiri, Madhava Krishna, Supreeth Achar
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: demo papers (2008)

In environments which possess relatively few features that enable a robot to unambiguous determine its location, global localization algorithms can result in multiple hypotheses locations for a robot which makes active guidance for localization necessary. When extended to multi robotic scenarios where all robots possess more than one hypothesis of their position, there is the opportunity to do better by using robots apart from obstacles as 'hypotheses resolving agents'. The demo here showcases a unified framework accounting for the map structure as well as measurement amongst robots while guiding a set of robots to positions where they can localize to a unique state. Another aspect of framework demonstrates the idea of dispatching localized robots to locations where they can assist a maximum of the remaining unlocalized robots to overcome their ambiguity. The method presented has been tested in both simulation and real-time on robots and its efficacy verified.
Efficient Collective Communication Paradigms for Hyperspectral Imaging Algorithms Using HeteroMPI
Authors: David Valencia, Antonio Plaza, Vladimir Rychkov, Alexey Lastovetsky
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

Most of the parallel strategies used for information extraction in remotely sensed hyperspectral imaging applications have been implemented in the form of parallel algorithms on both homogeneous and heterogeneous networks of computers. In this paper, we develop a study on efficient collective communications based on the usage of HeteroMPI for a parallel heterogeneous hyperspectral imaging algorithm which uses concepts of mathematical morphology.
A Study on the Ubiquitous Wellbeing System Design and Implementation Using Wireless Bio-Signal Sensor
Authors: Yang-Jae Park, Nam-Il Kim, Un-Gu Kang, Sung-Kwan Kang
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

As pervasive or ubiquitous computing matures, researchers and developers look for areas of application of this promising technology that can improve the quality of our lives. The "Healthcare" and "Home" is the best environments, so we focused the effective and undeveloped area in Ubiquitous Healthcare Service in Home. People spend more time in their homes than in any other space. The home ideally provides a safe, comfortable environment in which to relax, communicate, learn, and be entertained. Because of these reasons home environment is the best place for a chronic disease patient. As the standard of living rises, people are more interested in their health and desire well-being life. However they cannot make sufficient effort regarding their health and life style due to the fast moving working environment. In order to attain their sound life, it is necessary for people to have support from user customized life management service. The most prominent features of this system are rule based clinical decision supporting, life style recommendation based on user's vital signs, existence of chronic disease, life pattern and family history, as well as life style enhancement promoting service that induces user to accomplish their mental and physical healthiness based on the recommendations. The prototype system is designed and implemented using smart objects such as smart mirror and smart picture frame. The doctor side application is also built to enable medical doctors to examine systems' appropriateness of clinical use.
Probabilistic Discrete Mixtures Colour Texture Models
Authors: Michal Haindl, Vojtĕch Havlíček, Jiří Grim
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

A new generative multispectral texture model based on discrete distribution mixtures is introduced. Statistical texture properties are represented by a discrete distribution mixture of product components. A natural colour or multispectral texture is spectrally factorized and discrete mixtures models are learned and used to synthesize single orthogonal monospectral components. Texture synthesis is based on easy computation of arbitrary conditional distributions from the model. Finally single synthesized monospectral texture components are transformed into the required synthetic colour texture. This model can easily serve for texture segmentation, retrieval or to model single factors in complex Bidirectional Texture Function (BTF) space models. The advantages and weak points of the presented approach are demonstrated on several colour texture applications.
C# and the .NET Framework: Ready for Real Time?
Authors: Michael H. Lutz, Phillip A. Laplante
Venue: IEEE Software (2003)

Microsoft's next-generation platform, the .NET Framework, offers a new language, C#, which aims to offer the power of C++ with the ease of Visual Basic. In this article, the authors consider the application of C# and the .NET Framework to real-time systems. Their performance tests show that C and C# performance is comparable in some cases. However, they show that C# is not currently suitable for hard real-time applications and should be used for firm and soft real-time applications only with care.
A Two Stage Energy Model Exhibiting Selectivity to Changing Disparity
Authors: Xiaojiang Guo, Bertram E. Shi
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

We show that by cascading the disparity energy model and the motion energy model, we obtain neurons that are selective for changing disparity, which is a cue that biological systems may use in the perception of stereo-motion. We demonstrate that the outputs of this model exhibit joint tuning to disparity and stereo-motion. The output achieves a peak response for an input with a preferred disparity that also changes at a preferred rate. The joint tuning curve in the disparity---change of disparity space is approximately separable. We further demonstrate that incorporating a normalization step between the two stages reduces the variability of the model output.
A MSM-PGA Based on Multi-agent for Solving TSP
Authors: Tinghong Zhao, Zibin Man, Xueyi Qi
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

TSP (Traveling Salesman Problem) is a typical combinational optimization problem. At present, there are a lot of methods to solve this problem, but with the increase of the scale of this problem, most methods face the difficult problem of "combination exploding". This paper combines Multi-Agent theory and MSM-PGA (Master-slaver Model Parallel Genetic Algorithm) together, form one MSM-PGA Multi-Agent union. This union solves the TSP by the coordination between many Agents inside the union. The introduction of Multi-Agent theory, make the master course and slave course of MSM-PGA to be made of Agent, so the ability of communication and coordination raise greatly, thus overcome the shortcoming of original MSM-PGA; And comparing with other methods solved TSP, the method of this paper has the fast computational speed and the high precision, and not only has overcome the difficult problem of "combination exploding" but also can get more optimal solving than other algorithms.
The Erdős--Hajnal conjecture for bull-free graphs
Authors: Maria Chudnovsky, Shmuel Safra
Venue: Journal of Combinatorial Theory Series B (2008)

The bull is a graph consisting of a triangle and two pendant edges. A graphs is called bull-free if no induced subgraph of it is a bull. In this paper we prove that every bull-free graph on n vertices contains either a clique or a stable set of size n^1^4, thus settling the Erdos-Hajnal conjecture [P. Erdos, A. Hajnal, Ramsey-type theorems, Discrete Appl. Math. 25 (1989) 37-52] for the bull.
Using insurance to increase internet security
Authors: Svetlana Radosavac, James Kempf, Ulaş C. Kozat
Venue: Proceedings of the 3rd international workshop on Economics of networked systems (2008)

Managing security risks in the Internet has so far mostly involved methods to reduce the risks and the severity of the damages. Those methods reduce but do not eliminate risk, and the question remains on how to handle the residual risk. Current schemes applied by Internet Service Providers (ISPs) penalize the users, who suffer from the consequences. In this paper, we take a new approach to the problem of Internet security and advocate managing the residual risk by buying insurance against it and consequently re-arranging the incentive chain. We first analyze the current state of the Internet and investigate if it is possible to alleviate the existing problems by introducing insurance schemes. By performing detailed analysis we define an insurance policy that can survive in a competitive market. Following that, we analyze the impact of insurance-based ISPs on the rest of the network and attempt to answer whether using insurance can increase the overall security of the system and provide incentive to other ISPs to implement such policies.
Novel Phylogenetic Network Inference by Combining Maximum Likelihood and Hidden Markov Models
Authors: Sagi Snir, Tamir Tuller
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

Horizontal Gene Transfer (HGT) is the event of transferring genetic material from one lineage in the evolutionary tree to a different lineage. HGT plays a major role in bacterial genome diversification and is a significant mechanism by which bacteria develop resistance to antibiotics. Although the prevailing assumption is of complete HGT, cases of partial HGT (which are also named chimeric HGT) where only part of a gene is horizontally transferred, have also been reported, albeit less frequently.In this work we suggest a new probabilistic model for analyzing and modeling phylogenetic networks, the NET-HMM. This new model captures the biologically realistic assumption that neighboring sites of DNA or amino acid sequences are not independent, which increases the accuracy of the inference. The model describes the phylogenetic network as a Hidden Markov Model (HMM), where each hidden state is related to one of the network's trees. One of the advantages of the NET-HMM is its ability to infer partial HGT as well as complete HGT. We describe the properties of the NET-HMM, devise efficient algorithms for solving a set of problems related to it, and implement them in software. We also provide a novel complementary significance test for evaluating the fitness of a model (NET-HMM) to a given data set.Using NET-HMM we are able to answer interesting biological questions, such as inferring the length of partial HGT's and the affected nucleotides in the genomic sequences, as well as inferring the exact location of HGT events along the tree branches. These advantages are demonstrated through the analysis of synthetical inputs and two different biological inputs.
Ministers of parliament and information and communication technologies as a means of horizontal and vertical communication in Western Europe
Authors: Gustavo Cardoso, Carlos Cunha, Susana Nascimento
Venue: Information Polity (2004)

The analysis in this article focuses on the vertical and horizontal communication patterns of MPs, drawing on examples from a comparative survey done in seven European countries. The results show that the MPs in these countries can still be said to be in an initial phase of exploiting the full range of these new technologies to support their parliamentary and partisan activity, and that traditional media such as television, radio and newspapers are still the favoured means for political communication. In so far as ICT is used, MPs primarily use these means for internal communication within the party or within parliament, and not very much for external communication with constituents, journalists, lobbyists, etc. Analysing the use of homepages and political campaign via ICT, both of these means are seen to be largely dependent on the political party of the MP, and the party's electoral strategies, limiting individual initiatives by MPs. Also, a certain disinterest in a more extensive use, of ICT on the part of the MPs was found. There seem to be a number of reasons for this disinterest, among these the argument that there is still a considerable digital divide especially in the Southern European countries. However, as computer and Internet diffusion continues to increase rapidly, this argument becomes increasingly invalid.
Security Property Violation in CPS through Timing
Authors: Han Tang, Bruce M. McMillin
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

Security in a Cyber-Physical System (CPS) is not well understood. Interactions between components in the Cyber and Physical domains lead to unintended information flow. This paper makes use of formal information flow models to describe leakage in a model CPS, the Cooperating FACTS Power System. Results show that while a casual observer cannot ascertain confidential internal information, when application semantics, including timing, are considered, this confidentiality is lost. Model checking is used to verify the result. The significance of the paper is in showing an example of the complex interactions that occur between the Cyber and Physical domains and their impact on security.
Second Order Conditioning in the Sub-cortical Nuclei of the Limbic System
Authors: Adedoyin Maria Thompson, Bernd Porr, Christoph Kolodziejski, Florentin Wörgötter
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

Three factor Isotropic sequence order (ISO3) learning is a form of differential Hebbian learning where a third factor switches on learning at relevant moments for example, after reward retreival. This switch enables learning only at specific moments and, thus, stablises the corresponding weights. The concept of using a third factor as a gating signal for learning at relevant moments has been extended in this paper to perform second order conditioning (SOC). We present a biological model of the sub-cortical nuclei of the limbic system that is capable of performing SOC in a food seeking task. The 3rd-factor is modelled by dopaminergic neurons of the VTA which are activated via a direct excitatory glutamatergic pathway, and an indirect dis-inhibitory GABAergic pathway. The latter generates an amplification in the number of tonically active DA neurons. This produces an increase in DA outside the event of a primary reward and enables SOC to be accomplished.
A pioneer woman
Authors: Michael Ross
Venue: Communications of the ACM (2009)

Programmer Jean Bartik is inducted into the Computer History Museum's Hall of Fellows.
Consistency-driven data quality management of networked sensor systems
Authors: Kewei Sha, Weisong Shi
Venue: Journal of Parallel and Distributed Computing (2008)

With more and more real deployments of wireless sensor network applications, we envision that their success is nonetheless determined by whether the sensor networks can provide a high quality stream of data over a long period. In this paper, we propose a consistency-driven data quality management framework called Orchis that integrates the quality of data into an energy efficient sensor system design. Orchis consists of four components, data consistency models, adaptive data sampling and process protocols, consistency-driven cross-layer protocols and flexible APIs to manage the data quality, to support the goals of high data quality and energy efficiency. We first formally define a consistency model, which not only includes temporal consistency and numerical consistency, but also considers the application-specific requirements of data and data dynamics in the sensing field. Next, we propose an adaptive lazy energy efficient data collection protocol, which adapts the data sampling rate to the data dynamics in the sensing field and keeps lazy when the data consistency is maintained. Finally, we conduct a comprehensive evaluation to the proposed protocol based on both a TOSSIM-based simulation and a real prototype implementation using MICA2 motes. The results from both simulation and prototype show that our protocol reduces the number of delivered messages, improves the quality of collected data, and in turn extends the lifetime of the whole network. Our analysis also implies that a tradeoff should be carefully set between data consistency requirements and energy saving based on the specific requirements of different applications.
Ordering Cellular Spaces with Application to Curves and Knots
Authors: Anatoly B. Korchagin
Venue: Discrete Computational Geometry (2008)

This paper concerns the problem of ordering geometrical objects, which have the structure of finite cellular spaces. We introduce cellular codes, cellular indices, and (k,l)-sizes and apply them to ordering 2-cells, plane curves, and projections of knots. Results of this paper can be applied (1)&#x00a0;to ordering other geometrical objects with cellular space structures, (2)&#x00a0;in psychological and computer tests for comparison of complexity of geometrical objects, and (3)&#x00a0;to ordering objects with fractal and chaotic structure, which admit approximation by cellular spaces.
A Software Infrastructure for Multi-agent Geosimulation Applications
Authors: Ivan Blecic, Arnaldo Cecchini, Giuseppe A. Trunfio
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

In this paper we present characteristics, features and computational strategies used in MAGI (Multi-Agent Geosimulation Infrastructure) which are relevant for strongly geo-spatially oriented agent-based simulations. These characteristics make MAGI an effective modelling and simulation environment, in terms of generality, user friendliness, modelling flexibility, interoperability with GIS datasets and computational efficiency. The infrastructure is composed of a development environment for building and executing simulation models, and a class library based on open source components. Differently from most of the existing tools for geosimulation, both raster and vector representation of simulated entities are allowed and managed with efficiency. This is obtained through the integration of a geometry engine implementing a core set of operations on spatial data through robust geometric algorithms, and an efficient spatial indexing strategy for moving agents.
Impact of sensor-enhanced mobility prediction on the design of energy-efficient localization
Authors: Chuang-Wen You, Polly Huang, Hao-hua Chu, Yi-Chao Chen, Ji-Rung Chiang, Seng-Yong Lau
Venue: Ad Hoc Networks (2008)

Energy efficiency and positional accuracy are often contradictive goals. We propose to decrease power consumption without sacrificing significant accuracy by developing an energy-aware localization that adapts the sampling rate to target's mobility level. In this paper, an energy-aware adaptive localization system based on signal strength fingerprinting is designed, implemented, and evaluated. Promising to satisfy an application's requirements on positional accuracy, our system tries to adapt its sampling rate to reduce its energy consumption. The contribution of this paper is fourfold. (1) We have developed a model to predict the positional error of a real working positioning engine under different mobility levels of mobile targets, estimation error from the positioning engine, processing and networking delay in the location infrastructure, and sampling rate of location information. (2) In a real test environment, our energy-saving method solves the mobility estimation error problem by utilizing additional sensors on mobile targets. The result is that we can improve the prediction accuracy by 56.34% on average, comparing to algorithms without utilizing additional sensors. (3) We further enhance our sensor-enhanced mobility prediction algorithm by detecting the target's moving foot step and then estimate the target's velocity. This method can improve the mobility prediction accuracy by 49.81% on an average, comparing to previous sensor-enhanced mobility prediction algorithm. (4) We implemented our energy-saving methods inside a working localization infrastructure and conducted performance evaluation in a real office environment. Our performance results show as much as 68.92% reduction in power consumption.