ppxscal/embedding_network huggingface dataset:
Cross-layer Routing Design in Cognitive Radio Networks by Colored Multigraph Model
Authors: Xianwei Zhou, Lin Lin, Jianping Wang, Xuesong Zhang
Venue: Wireless Personal Communications: An International Journal (2009)

In this paper, the cross-layer design routing in cognitive radio(CR) networks is studied. We propose a colored multigraph based model for the temporarily available spectrum bands, called spectrum holes in this paper. Based on this colored multigraph model, a polynomial time algorithm with complexity O(n 2) is also proposed to develop a routing and interface assignment, where n is the number of nodes in a CR network. Our algorithm optimizes the hop number of routing, meanwhile, the adjacent hop interference (AHI) is also optimized locally.
Performance Analysis of Blind Multiuser Detector with Fuzzy Kalman Filter in IR-UWB
Authors: Peng Jian, Su Li-yun
Venue: International Journal of Distributed Sensor Networks (2009)

With on-going widespread deployment of UWB systems, multi-user detection has received increasing attention. In order to successfully decode the users in a UWB system, the most important issue is to be solved, apart from the multi-path and multiple-access channel. Most existing approaches employ correlators to correlate the received signal with a template signal. This technique appears very powerful, but not so satisfactory in a multi-path and multiple-access channel. A novel multi-user detection algorithm relying on the theory of canonical representation of multi-user receivers and fuzzy Kalman filtering (FKF) is proposed for impulse radio ultra-wideband systems. Dynamical systems of time-hopping BPSK in ultra-wideband are developed separately in the paper. Although the Kalman filtering algorithm is conditioned on perfect knowledge of some system parameters, we have used the fuzzy technique to overcome the difficulties. It is presumed that both, the process noise and the measurement noise, are zero-mean white sequences with their known covariance. If the Kalman filter is based on a complete and perfect model, the innovation should be a zero-mean white noise process, otherwise there is something erroneous with the design and the filter is not performing optimally, thus making the filter to diverge or coverage to a large bound. In practice, it is difficult to know the exact values for covariance. In order to reduce computation, we have to ignore some errors, but sometimes those unmodeled errors will remain significant. The adaptation of the filter uses a fuzzy inference system based on a covariance matching scheme that adjusts the measurement noise covariance matrix online. The basic idea behind this technique is to make the residual consistent with their theoretical covariance. The fuzzy Kalman filter method is proposed in the previous subsection is related to many existing algorithms for adaptive multiuser detector. Now, some performances are given to compare the differences from other prior algorithms. Since the Kalman filter scheme and the RLS one are similar, it is necessary to compare the proposed algorithm with the before RLS algorithms. Theoretical analysis and numerical results show that the new scheme has a better bit error rate performance compared with the conventional detector, and the effectiveness of the novel Kalman filtering algorithm.
Reasoning about preferences in argumentation frameworks
Authors: Sanjay Modgil
Venue: Artificial Intelligence (2009)

The abstract nature of Dung's seminal theory of argumentation accounts for its widespread application as a general framework for various species of non-monotonic reasoning, and, more generally, reasoning in the presence of conflict. A Dung argumentation framework is instantiated by arguments and a binary conflict based attack relation, defined by some underlying logical theory. The justified arguments under different extensional semantics are then evaluated, and the claims of these arguments define the inferences of the underlying theory. To determine a unique set of justified arguments often requires a preference relation on arguments to determine the success of attacks between arguments. However, preference information is often itself defeasible, conflicting and so subject to argumentation. Hence, in this paper we extend Dung's theory to accommodate arguments that claim preferences between other arguments, thus incorporating meta-level argumentation based reasoning about preferences in the object level. We then define and study application of the full range of Dung's extensional semantics to the extended framework, and study special classes of the extended framework. The extended theory preserves the abstract nature of Dung's approach, thus aiming at a general framework for non-monotonic formalisms that accommodate defeasible reasoning about as well as with preference information. We illustrate by formalising argument based logic programming with defeasible priorities in the extended theory.
A Dynamic Model for On-Line Social Networks
Authors: Anthony Bonato, Noor Hadi, Paul Horn, Paweł Prałat, Changping Wang
Venue: Proceedings of the 6th International Workshop on Algorithms and Models for the Web-Graph (2009)

We present a deterministic model for on-line social networks based on transitivity and local knowledge in social interactions. In the Iterated Local Transitivity (ILT) model, at each time-step and for every existing node x, a new node appears which joins to the closed neighbour set of x. The ILT model provably satisfies a number of both local and global properties that were observed in real-world on-line social and other complex networks, such as a densification power law, decreasing average distance, and higher clustering than in random graphs with the same average degree. Experimental studies of social networks demonstrate poor expansion properties as a consequence of the existence of communities with low number of inter-community links. A spectral gap for both the adjacency and normalized Laplacian matrices is proved for graphs arising from the ILT model, thereby simulating such bad expansion properties.
GTPP: general truncated pyramid architecture over P2PSIP networks
Authors: Zhonghong Ou, Erkki Harjula, Mika Ylianttila
Venue: Proceedings of the International Conference on Mobile Technology, Applications, and Systems (2008)

There is recently some research work focusing on the multiple-level hierarchical overlay architecture in peer-to-peer (P2P) SIP networks with some assumptions. But questions such as what performance improvements can be achieved and how many levels should be existed in the architecture have not been proved from the mathematical aspect. In this paper, a general truncated pyramid architecture over P2PSIP networks (GTPP) has been put forward in which the number of peers of each level of sub-overlay is subject to the negative exponential distribution (NED) according to the maximum information entropy theorem. Utilizing the similarity between geometric distribution (GD) and NED, we harness GD to distribute peers into multiple sub-overlays to convert the distribution function into discrete domain. Through mathematical evaluation, we get the conclusion that 2~4 levels of sub-overlays are appropriate for most of the systems which also takes the maintenance cost into consideration. As for the number of peers in each sub-sub-overlay (SSO), the kth root of the total number of peers N, that is to say, n = N1/k, is a proper number taking the load balancing into account, wherein k stands for the total number of levels of GTPP.
Numeric control machine tool technology and applications
Authors: James Warner, Ronald L. Boase
Venue: Proceedings of the May 6-10, 1974, national computer conference and exposition (1974)

The problem of constructing a part family code for identifying parts having "similar" process plans is considered. The basic emphasis is on the role the part family code plays in relating descriptive information on the part to its process plan. The use of the typical digital structure of a part family code restricts the ability for representing this relationship accurately. Self-learning computer algorithms which express this relationship in functional form replaces the need for a part family code. Code identifiers labeling parts having similar process plans can then be more beneficially used.
Stability and existence of periodic solutions to delayed Cohen-Grossberg BAM neural networks with impulses on time scales
Authors: Yongkun Li, Xuerong Chen, Lu Zhao
Venue: Neurocomputing (2009)

In this paper, by using the continuation theorem of coincidence degree theory and constructing some suitable Lyapunov functions, we study the stability and existence of periodic solutions to delayed Cohen-Grossberg BAM neural networks with impulses on time scales.
A study on the effect of work environment perception on user satisfaction in health information systems: HISs quality as mediator
Authors: Chung-Hung Tsai, Dauw-Song Zhu
Venue: International Journal of Information Technology and Management (2009)

This purpose of this study is to develop the user satisfaction model of Health Information Systems (HISs). A survey of 252 samples of the medical centre in Taiwan shows that the effects of user involvement and supervisor support on user satisfaction are mediated by HISs quality. Besides, service quality has the most influence on user satisfaction in HISs quality. This research can provide managers of the hospital with the implication that we must focus not only on the Information System (IS) quality aspect (system quality, information quality), but also on the social interaction aspect (user involvement, supervisor support) and technical support aspect (service quality).
Identifying functional connectivity in large-scale neural ensemble recordings: A multiscale data mining approach
Authors: Seif Eldawlatly, Rong Jin, Karim G. Oweiss
Venue: Neural Computation (2009)

Identifying functional connectivity between neuronal elements is an essential first step toward understanding how the brain orchestrates information processing at the single-cell and population levels to carry out biological computations. This letter suggests a new approach to identify functional connectivity between neuronal elements from their simultaneously recorded spike trains. In particular, we identify clusters of neurons that exhibit functional interdependency over variable spatial and temporal patterns of interaction. We represent neurons as objects in a graph and connect them using arbitrarily defined similarity measures calculated across multiple timescales. We then use a probabilistic spectral clustering algorithm to cluster the neurons in the graph by solving a minimum graph cut optimization problem. Using point process theory to model population activity, we demonstrate the robustness of the approach in tracking a broad spectrum of neuronal interaction, from synchrony to rate co-modulation, by systematically varying the length of the firing history interval and the strength of the connecting synapses that govern the discharge pattern of each neuron. We also demonstrate how activity-dependent plasticity can be tracked and quantified in multiple network topologies built to mimic distinct behavioral contexts. We compare the performance to classical approaches to illustrate the substantial gain in performance.
Software-driven sensor networks for short-range shallow water applications
Authors: Raja Jurdak, Pierre Baldi, Cristina Videira Lopes
Venue: Ad Hoc Networks (2009)

Most existing underwater networks target deep and long range oceanic environments, which has led to the design of power hungry and expensive underwater communication hardware. Because of prohibitive monetary and energy cost of currently over-engineered communication hardware, dense deployments of shallow water sensor networks remain an elusive goal. To enable dense shallow water networks, we propose a network architecture that builds on the success of terrestrial sensor motes and that relies on the coupling of software modems and widely available speakers and microphones in sensor motes to establish acoustic communication links. In this paper, we analytically and empirically explore the potential of this acoustic communication system for the underwater environment. Our experimental approach first profiles the hardware in water after waterproofing the components with elastic membranes. The medium profiling results expose the favorable frequencies of operation for the hardware, enabling us to design a software FSK modem. Subsequently, our experiments evaluate the data transfer capability of the underwater channel with 8-frequency FSK software modems. The experiments within a 17x8m controlled underwater environment yield an error-free channel capacity of 24bps, and they also demonstrate that the system supports date rates between 6 and 48bps with adaptive fidelity.
Using Markov Chain Monte Carlo to quantify parameter uncertainty and its effect on predictions of a groundwater flow model
Authors: Ahmed E. Hassan, Hesham M. Bekhit, Jenny B. Chapman
Venue: Environmental Modelling Software (2009)

A statistical Bayesian framework is used to solve the inverse problem and develop the posterior distributions of parameters for a density-driven groundwater flow model. This Bayesian approach is implemented using a Markov Chain Monte Carlo (MCMC) sampling method. Three sets of data pertaining to the location of the freshwater-seawater transition zone exist for the site, including chemistry data, hydraulic head data and newly collected magnetotelluric (MT) data. A sequential conditioning approach is implemented where the chemistry data and MT-converted salinity are combined as a single data set and are used to first condition the parameter distributions. The head data are subsequently used as a second conditioning data set where the posterior distribution developed by the first conditioning is used as a prior for this second conditioning. Results of this analysis indicate that conditioning on the available data sets yields dramatic reduction of uncertainty compared to unconditioned simulations, especially for the recharge-conductivity ratio. This ratio controls the location of the transition zone, and the conditioning results in a smaller range of variability compared to the distribution used in previous modelling of the site. Using the conditioned distributions to solve the density-driven flow problem in a stochastic framework (i.e., model parameters are randomly sampled from the posterior distributions) results in a range of output flow fields that is much narrower than the previous model. The ensemble mean of these solutions and the uncertainty bounds expressed by the mean+/-one standard deviation lie within the uncertainty bounds of the original model. For the case study shown here, the effect of conditioning data is dominant over the effect of prior information.
Platform Support for Situated Collaborative Learning
Authors: Surya Bahadur Kathayat, Rolv Bræk
Venue: Proceedings of the 2009 International Conference on Mobile, Hybrid, and On-line Learning (2009)

In this paper, we consider the situated and collaborative learning domain, where students (as members of groups) go around the city and collaborate to learn. They are dependent on each other and need to collaborate to accomplish tasks. A treasure hunt game has been developed as a case study to help analyzing the domain and designing generic and flexible platform support for situate collaborative learning. The resulting platform seeks to support the domain as directly as possible by using agents to represent domain entities and providing services as collaboration among roles played by agents. The paper identifies stable and variable parts and explains how the necessary flexibility can be provided.
Impact of qualification management on scheduling in semiconductor manufacturing
Authors: Carl Johnzén, Philippe Vialletelle, Stéphane Dauzère-Pérès, Claude Yugma, Alexandre Derreumaux
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

A qualification management software that proposes recipe qualifications on tools in toolsets for semiconductor manufacturing has been developed. The qualification proposals are based on flexibility measures that have been shown to model capacity allocation in semiconductor workshops. In this paper, qualifications are used in order to see how increased flexibility for the capacity allocation improve scheduling. For this a scheduler simulator for the photolithography area has been used. Tests prove that qualifications -- if they are well managed -- both enable the simulator to achieve better scheduling and enable toolsets to be less sensitive to tool breakdowns.
A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems
Authors: Ran Wolff, Kanishka Bhaduri, Hillol Kargupta
Venue: IEEE Transactions on Knowledge and Data Engineering (2009)

In a large network of computers or wireless sensors, each of the components (henceforth, peers) has some data about the global state of the system. Much of the system's functionality such as message routing, information retrieval and load sharing relies on modeling the global state. We refer to the outcome of the function (e.g., the load experienced by each peer) as the \emph{model} of the system. Since the state of the system is constantly changing, it is necessary to keep the models up-to-date. Computing global data mining models e.g. decision trees, $k$-means clustering in large distributed systems may be very costly due to the scale of the system and due to communication cost, which may be high. The cost further increases in a dynamic scenario when the data changes rapidly. In this paper we describe a two step approach for dealing with these costs. First, we describe a highly efficient \emph{local} algorithm which can be used to monitor a wide class of data mining models. Then, we use this algorithm as a feedback loop for the monitoring of complex functions of the data such as its $k$-means clustering. The theoretical claims are corroborated with a thorough experimental analysis.
An alpha-activity-based binaural beat sound entrainment system using arousal state model
Authors: Sittapong Settapat, Michiko Ohkura
Venue: Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology (2008)

We developed a new real-time control system for customizing an auditory stimulus (the binaural beat sound) by judging a user's alpha waves to entrain his/her feeling in the most relaxed way. We use an autoregressive forecasting model to estimate the frequency response series of the alpha frequency bands and a fuzzy logic controller to regulate the binaural beat control signal on a forecasting error signal. The arousal state determination model plays a role in regulating an appropriate binaural beat sound correlating with a change in alpha activity. According to studies of the relationship between arousal state and alpha activity, the alpha activity level may state-dependent, which can be modeled following the "inverted-U" model. The inverted-U concept is employed to determine the user arousal state, and tries to understand the user arousal state through the change in alpha activity. From the results of experiments, it is confirmed that the inverted-U model for arousal state determination is an effective model to regulate a stimulus properly with the determined arousal state.
Applications and extensions of the TENEX operating system
Authors: Jerry D. Burchfiel, Mel Pirtle, Edward Fiala, Robert Thomas, Daniel Murphy, David Walden
Venue: Proceedings of the May 6-10, 1974, national computer conference and exposition (1974)

The TENEX system was developed in 1969 to serve as a powerful, flexible, yet inexpensive research facility. It provides virtual memory, a hierarchy of processes within each job, a pseudointerrupt system for interprocess communication, and a highly human-engineered command language. This system has become such a popular research tool that there are (as of January 1974) 12 TENEX systems in operation. Ten of these TENEX systems are hosts on the ARPANET, a national computer resource sharing network developed by the D.O.D. Advanced Research Projects Agency.
Feedback Adaptive Routing Algorithm for DTN
Authors: Shen Ling, Wu Wei
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 02 (2009)

Routing in DTN is a considerably different and more challenging problem. In this paper, we propose a feedback adaptive routing algorithm. Nodes evaluate routing influence of other nodes in the network based on the feedback of routing results. and first transmit messages through nodes with higher influence factor.The experiment shows that the high performance nodes transmit the majority messages, and the majority of nodes do not need to save too many messages. The algorithm can achieve high delivery ratio and save node buffers.
Dependent advice: a general approach to optimizing history-based aspects
Authors: Eric Bodden, Feng Chen, Grigore Rosu
Venue: Proceedings of the 8th ACM international conference on Aspect-oriented software development (2009)

Many aspects for runtime monitoring are history-based: they contain pieces of advice that execute conditionally, based on the observed execution history. History-based aspects are notorious for causing high runtime overhead. Compilers can apply powerful optimizations to history-based aspects using domain knowledge. Unfortunately, current aspect languages like AspectJ impede optimizations, as they provide no means to express this domain knowledge. In this paper we present dependent advice, a novel AspectJ language extension. A dependent advice contains dependency annotations that preserve crucial domain knowledge: a dependent advice needs to execute only when its dependencies are fulfilled. Optimizations can exploit this knowledge: we present a whole-program analysis that removes advice-dispatch code from program locations at which an advice's dependencies cannot be fulfilled. Programmers often opt to have history-based aspects generated automatically, from formal specifications from model-driven development or runtime monitoring. As we show using code-generation tools for two runtime-monitoring approaches, tracematches and JavaMOP, such tools can use knowledge contained in the specification to automatically generate dependency annotations as well. Our extensive evaluation using the DaCapo benchmark suite shows that the use of dependent advice can significantly lower, sometimes even completely eliminate, the runtime overhead caused by history-based aspects, independently of the specification formalism.
Legal aspects of computer management
Authors: Susan H. Nycum
Venue: Proceedings of the May 19-22, 1975, national computer conference and exposition (1975)

The area "Legal Aspects" has particular appeal to computer supervisors and managers, facility directors, comptrollers, personnel and labor relations officers and others concerned with the management responsibilities of computer technology.
Market coverage and "love of software variety" in the supporting services approach
Authors: Dachrahn Wu, Ming Chung Chang, Mei-Hua Chang
Venue: Netnomics (2008)

This paper uses a model of system product monopoly to examine the supporting services approach in network economics. We find that the monopoly sets the software price at the average cost of developing each variety of software. Furthermore, if the function defined for "love of software variety" exhibits too much "love of variety of software," then there exists only the boundary solution that corresponds to full market coverage. We also show that if the market is partially covered, then there always exist positive network externalities. However, if the market is fully covered, then network externalities vanish.