ppxscal/embedding_network huggingface dataset:
Queuing network models for delay analysis of multihop wireless ad hoc networks
Authors: Nabhendra Bisnik, Alhussein A. Abouzeid
Venue: Ad Hoc Networks (2009)

In this paper we analyze the average end-to-end delay and maximum achievable per-node throughput in random access multihop wireless ad hoc networks with stationary nodes. We present an analytical model that takes into account the number of nodes, the random packet arrival process, the extent of locality of traffic, and the back off and collision avoidance mechanisms of random access MAC. We model random access multihop wireless networks as open G/G/1 queuing networks and use the diffusion approximation in order to evaluate closed form expressions for the average end-to-end delay. The mean service time of nodes is evaluated and used to obtain the maximum achievable per-node throughput. The analytical results obtained here from the queuing network analysis are discussed with regard to similarities and differences from the well established information-theoretic results on throughput and delay scaling laws in ad hoc networks. We also investigate the extent of deviation of delay and throughput in a real world network from the analytical results presented in this paper. We conduct extensive simulations in order to verify the analytical results and also compare them against NS-2 simulations.
Two-step filtering datamining method integrating case-based reasoning and rule induction
Authors: Yoon-Joo Park, Enmi Choi, Soo-Hyun Park
Venue: Expert Systems with Applications: An International Journal (2009)

Case-based reasoning (CBR) methods are applied to various target problems on the supposition that previous cases are sufficiently similar to current target problems, and the results of previous similar cases support the same result consistently. However, these assumptions are not applicable for some target cases. There are some target cases that have no sufficiently similar cases, or if they have, the results of these previous cases are inconsistent. That is, the appropriateness of CBR is different for each target case, even though they are problems in the same domain. Thus, applying CBR to whole datasets in a domain is not reasonable. This paper presents a new hybrid datamining technique called two-step filtering CBR and rule induction (TSFCR), which dynamically selects either CBR or RI for each target case, taking into consideration similarities and consistencies of previous cases. We apply this method to three medical diagnosis datasets and one credit analysis dataset in order to demonstrate that TSFCR outperforms the genuine CBR and RI.
An agrometeorological approach for the simulation of Plasmopara viticola
Authors: S. Orlandini, L. Massetti, A. Dalla Marta
Venue: Computers and Electronics in Agriculture (2008)

Agrometeorology can be applied to the analysis and modelling of plant disease development and creating a decision-support system for the operational management of crop protection. An approach for the simulation of grapevine (Vitis vinifera) downy mildew (Plasmopara viticola) is described in this paper. Mathematical models for grapevine leaf area growth and downy mildew development and infection have been proposed and integrated. The inputs to the models are represented by the fundamental agrometeorological variables of air temperature (^oC), relative humidity (%), rainfall (mm) and leaf wetness (0-1), and tuning parameters have been included to calibrate the models for any possible behaviour differences in the patho-system. The main outputs of the model are infection intensity during the growing season, and the timing of the different infection events. The research was conducted in Tuscany (Central Italy) where, since 1995, an experimental vineyard of Sangiovese variety has been monitored for the presence of the disease, and a standard station has been established for agrometeorological data collection. The model was calibrated on data collected in 1995 and 1996 and then applied and validated on an independent data set collected from 1998 to 2003. The results presented in this paper demonstrate how, based on the biology of both host and pathogen, the simulation calculated leaf area growth and the dynamics of disease infections during the season, giving an accurate description of the field situation.
An algebraic condition for product form in stochastic automata networks without synchronizations
Authors: J. M. Fourneau, B. Plateau, W. J. Stewart
Venue: Performance Evaluation (2008)

We consider Stochastic Automata Networks (SANs) in continuous time and we prove a sufficient condition for the steady-state distribution to have product form. We consider synchronization-free SANs in which the transitions of one automaton may depend upon the states of the other automata. This model can represent efficiently multidimensional Markov chains whose transitions are limited to one component but whose rates may depend on the state of the chain. The sufficient condition we obtain is quite simple and our theorem generalizes former results on SANs as well as results on modulated Markovian queues, such as Boucherie's theory on competing Markov chain, on reversible queues considered by Kelly and on modulated Jackson queueing networks studied by Zhu. The sufficient condition and the proof are purely algebraic and are based on the intersection of kernels for a certain set of matrices.
A novel mechanism for radio capacity maximization during MBMS transmissions in B3G networks
Authors: Antonios Alexiou, Christos Bouras, Vasileios Kokkinos, Evangelos Rekkas
Venue: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems (2008)

This paper proposes a novel mechanism for efficient power control during multicast transmissions in Beyond 3rd Generation (B3G) mobile networks. The mechanism utilizes optimally the available power resources of Universal Mobile Telecommunication System (UMTS) base stations, resulting to network capacity maximization. The proposed mechanism is based on the concept of transport channels combination (point-to-point and/or point-to-multipoint radio bearers) in any cell/sector of the network in which Multimedia Broadcast/Multicast Service (MBMS) users are residing. In particular, the transport channel combination that minimizes the transmission power of the base station is selected for the transmission of the MBMS traffic to the corresponding cell. The mechanism is evaluated through several realistic scenarios and the results indicate the ability of the mechanism to utilize optimally the radio resources of the network. Furthermore, our approach is compared with several power control mechanisms existing in the bibliography, including the 3rd Generation Partnership Project (3GPP) approaches (presented in 3GPP TS 25.346 and 3GPP TR 25.922), in order to highlight the enhancements that it provides.
A Control-Theoretic and Game-Theoretic Approach to Information Asymmetry in MAS
Authors: Jiafang Wang, Zhiyong Feng, Chao Xu, Hui Wang, Qian Yang
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

Based on the ideas of modern control theory and methods of game theory, this paper presents a formal framework for dealing with information asymmetry in MAS. In the framework, a control theory based model is introduced to specify a communication process between two agents. In the process, an agent who is short of some information takes the initiative to request needed information from agent who has information, and both agents establish reasoning process related to these information. The reasoning process corresponds to state space of controlled system in control theory. Besides, input and output messages of both agents are identified in the reasoning process. A method based on game theory is employed in the framework to constrain the information hiding behaviors of agents in communication. The work presented here not only introduces a new perspective of information asymmetry in MAS, but also presents a way to deal with information asymmetry in a proactive manner.
Convergence analysis of sectional methods for solving breakage population balance equations-I: the fixed pivot technique
Authors: Jitendra Kumar, Gerald Warnecke
Venue: Numerische Mathematik (2008)

In this work we study the convergence of the fixed pivot techniques (Kumar and Ramkrishna Chem. Eng. Sci. 51, 1311&#x2013;1332, 1996) for breakage problems. In particular, the convergence is investigated on four different types of uniform and non-uniform meshes. It is shown that the fixed pivot technique is second order convergent on a uniform and non-uniform smooth meshes. Furthermore, it gives first order convergence on a locally uniform mesh. Finally the analysis shows that the method does not converge on a non-uniform random mesh. The mathematical results of convergence analysis are also validated numerically.
Distributed algorithms for stable and secure network coordinates
Authors: Guohui Wang, T.S. Eugene Ng
Venue: Proceedings of the 8th ACM SIGCOMM conference on Internet measurement (2008)

Since its inception, the concept of network coordinates has been proposed to solve a wide variety of problems such as overlay optimization, network routing, network localization, and network modeling. However, two practical problems significantly limit the applications of network coordinates today. First, how can network coordinates be stabilized without losing accuracy so that they can be cached by applications? Second, how can network coordinates be secured such that legitimate nodes' coordinates are not impacted by misbehaving nodes? Although these problems have been discussed extensively, solving them in decentralized network coordinates systems remains an open problem. This paper presents new distributed algorithms to solve the coordinates stability and security problems. For the stability problem, we propose an error elimination model that can achieve stability without hurting accuracy. A novel algorithm based on this model is presented. For the security problem, we show that recently proposed statistical detection mechanisms cannot achieve an acceptable level of security against even simple attacks. We propose to address the security problem in two parts. First, we show how the computation of coordinates can be protected by a customized Byzantine fault detection algorithm. Second, we adopt a triangle inequality violation detection algorithm to protect delay measurements. These algorithms can be integrated together to provide stable and secure network coordinates.
Systolic FFT Processors: A Personal Perspective
Authors: Earl E. Swartzlander,  Jr.
Venue: Journal of Signal Processing Systems (2008)

This paper provides a personal perspective on developments in the implementation of two systolic fast Fourier transform processors over the last 25 years and identifies some of the lessons learned. This has been a period of tremendous advancements in integrated circuit technology that is demonstrated by the resulting processors. The first processor is the Modular Transform Processor that was developed at TRW in the 1982---1984 time frame using VLSI technology. It is a set of six large circuit boards that computes 4,096-point fast Fourier transforms using 22-bit floating-point arithmetic at sustained data rates of 40 MSPS. The second processor is a single ASIC chip systolic FFT processor developed by the Mayo Foundation in the 2001---2002 time frame that computes 4,096-point FFTs using 16-bit fixed-point arithmetic at sustained data rates of 200 MSPS. Some thoughts on the future directions of systolic FFT processor development are offered. Future systems will compute large transforms (e.g., 16 K-point to 1 M-point) at high data rates (e.g., 500 MSPS to 1 GSPS), will employ more precise arithmetic (e.g., 32-bit single precision IEEE Standard floating-point arithmetic), will consume very low power (e.g., on the order of one watt) and will be realized on a single chip.
A new trust region method with adaptive radius
Authors: Zhen-Jun Shi, Jinhua Guo
Venue: Computational Optimization and Applications (2008)

In this paper we develop a new trust region method with adaptive radius for unconstrained optimization problems. The new method can adjust the trust region radius automatically at each iteration and possibly reduces the number of solving subproblems. We investigate the global convergence and convergence rate of this new method under some mild conditions. Theoretical analysis and numerical results show that the new adaptive trust region radius is available and reasonable and the resultant trust region method is efficient in solving practical optimization problems.
A dialogue approach to learning object descriptions and semantic categories
Authors: Hartwig Holzapfel, Daniel Neubig, Alex Waibel
Venue: Robotics and Autonomous Systems (2008)

Acquiring new knowledge through interactive learning mechanisms is a key ability for humanoid robots in a natural environment. Such learning mechanisms need to be performed autonomously, and through interaction with the environment or with other agents/humans. In this paper, we describe a dialogue approach and a dynamic object model for learning semantic categories, object descriptions, and new words acquisition for object learning and integration with visual perception for grounding objects in the real world. The presented system has been implemented and evaluated on the humanoid robot Armar III.
Ant colony optimization with parameter adaptation for multi-mode resource-constrained project scheduling
Authors: Chuan-Wen Chiang, Yu-Qing Huang, Wen-Yen Wang
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2008)

An effective algorithm capable of solving the multi-mode resource-constrained project scheduling problem (MRCPSP) is an essential component for project planning and control since it can fully exploit the available resources and minimize the makespan of a given project. The MRCPSP is extremely complex and is known to be NP-hard in the strong sense. On the basis of the principles of ant colony optimization (ACO), we therefore propose a constructive-oriented iterative algorithm to acquire satisfactory solutions of the MRCPSP within a reasonable amount of computation time. The proposed algorithm, namely ACO-MRCPSP, attempts to identify a project schedule with minimum completion time without violating precedence and resource constraints. ACO-MRCPSP is characterized by its use of a self-adaptive parameter control strategy to guide artificial ants to effectively construct feasible solutions for the MRCPSP. The performance of the proposed algorithm is evaluated by comparing it against other existing metaheuristic implementations, such as simulated annealing (SA) and genetic algorithms (GAs), in terms of overall completion time for a set of project instances obtained form the Project Scheduling Library (PSPLIB). Experimental results indicate that ACO-MRCPSP is a significant improvement compared with the previous attempts at solving the MRCPSP.
Punctuated equilibrium in a non-linear system of action
Authors: Jos Timmermans
Venue: Computational Mathematical Organization Theory (2008)

Coleman's equilibrium model of social development, the Linear System of Action, is extended to cover the dynamics of societal transitions. The model implemented has the characteristics of a dissipative system. A variation and selection algorithm favoring the retention of relatively dependent actors forces the system away from equilibrium, while exchange of control, according to Coleman the driving force behind social action, accounts for dissipation, pulling the social system back to equilibrium. This Non-linear System of Action self-organizes into a critical state, as confirmed by the robust power law distribution of exchange of control for a wide range of model sizes. Related punctuated equilibrium dynamics and structural change are of special interest, as these are closely connected to hypotheses on social dynamics developed in the literature on societal transitions.
Julian dates and introduced temporal error in remote sensing vegetation phenology studies
Authors: J. B. Thayn, K. P. Price
Venue: International Journal of Remote Sensing (2008)

Remote-sensing-based vegetation phenology studies are commonly used to study agriculture, forestry, species distributions, and the effect of climate change on vegetation. These studies utilize annual time series of NDVI data to characterize seasonal growth patterns. The NDVI data for most of these studies have been pre-processed using a maximum value compositing process to minimize contamination from clouds. A side effect of this process is a degradation of temporal data, since NDVI values are assigned to multiday periods rather than the specific date of image capture. In this study, the compositing process is examined to determine if there is a reliable pattern to pixel selection. Also, the magnitude of the introduced error is estimated by comparing vegetation phenology metrics calculated using the temporally degraded data and metrics calculated using the actual date of each pixel. The root mean square errors between these datasets ranged from 9.4 to 10.9 days, much larger than is acceptable for most phenology studies. We conclude that vegetation phenology studies must make use of accurate temporal data to characterize changes in vegetation seasonality.
Formalizing Multi-state Learning Dynamics
Authors: Daniel Hennes, Karl Tuyls, Matthias Rauterberg
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

This paper extends the link between evolutionary game theory and multi-agent reinforcement learning to multistate games. In previous work, we introduced piecewise replicator dynamics, a combination of replicators and piecewise models to account for multi-state problems. We formalize this promising proof of concept and provide definitions for the notion of average reward games, pure equilibrium cells and finally, piecewise replicator dynamics. These definitions are general in the number of agents and states. Results show that piecewise replicator dynamics qualitatively approximate multi-agent reinforcement learning in stochastic games.
Effects of leaf structure on reflectance estimates of chlorophyll content
Authors: Lydia Serrano
Venue: International Journal of Remote Sensing (2008)

Assessment of chlorophyll content is a valuable tool for agricultural and non-managed ecosystem studies, since it provides information on key vegetation properties that are, in turn, linked to net primary production. The effects of varying leaf structure (leaf thickness [LT], leaf mass area [LMA] and leaf mass density [LMD]) on reflectance-based chlorophyll indices were assessed using regression and correlation analyses for seven Mediterranean species. The chlorophyll indices used were: (1) corrected for differences in internal scattering, (2) corrected for differences in surface scattering and (3) based on first reflectance first derivatives. Within species, chlorophyll indices showed similar correlation with chlorophyll content (r 2 values larger than 0.80, p
Soft decision trees: A genetically optimized cluster oriented approach
Authors: Sanjay Kumar Shukla, M. K. Tiwari
Venue: Expert Systems with Applications: An International Journal (2009)

When descriptions of data values are too detailed, the computational complexities involved in mining useful knowledge from the database generally increases. This gives rise to the need of tools techniques which can reduce these complexities and mine the valuable information hidden behind the database. There exists number of such techniques viz. decision trees, neural networks, rough-set theory, rule induction, and case-based reasoning which are able to meet the aforesaid objective up to some extent. Each of these techniques has its advantages and limitations that motivate researchers to develop new tools for the mining tasks. In this paper, we have developed a novel methodology, genetically optimized cluster oriented soft decision trees (GCSDT), to glean vital information imbedded in the large databases. In contrast to the standard C-fuzzy decision trees, where granules are developed through fuzzy (soft) clustering, in the proposed architecture granules are developed by means of genetically optimized soft clustering. In the GCSDT architecture, GA ameliorates the difficulty of choosing an initialization for the fuzzy clustering algorithm and always avoids degenerate partitions. This provides an effective means for the optimization of clustering criterion, where an objective function can be illustrated in terms of cluster's center. Growth of the GCSDT is realized by expanding nodes of the tree, characterized by the highest inconsistency index of the information granules. In order to validate the proposed tree structure it has been deployed on synthetic and machine learning data sets. Moreover, Results are compared with those produced by standard C4.5 decision trees and C-fuzzy decision trees; further student t-test is applied to show that these differences in results are statistically significant.
Optimization of stability-constrained geometrically nonlinear shallow trusses using an arc length sparse method with a strain energy density approach
Authors: Glenn A. Hrinda, Duc T. Nguyen
Venue: Finite Elements in Analysis and Design (2008)

A technique for the optimization of stability-constrained geometrically nonlinear shallow trusses with snap-through behavior is demonstrated using the arc length method and a strain energy density approach within a discrete finite-element formulation. The optimization method uses an iterative scheme that evaluates the performance of the design variables and then updates them according to a recursive formula that is controlled by the arc length method. A minimum weight design is achieved when a uniform nonlinear strain energy density is found in all members. This minimal condition places the design load just below the critical-limit load that causes snap-through of the structure. The optimization scheme is programmed into a nonlinear finite-element algorithm to find the large strain energy at critical-limit loads. Examples of highly nonlinear trusses that are found in literature are presented to verify the method.
A multi-modal spoken dialog system for interactive TV
Authors: Rajesh Balchandran, Mark E. Epstein, Gerasimos Potamianos, Ladislav Seredi
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

In this demonstration we present a novel prototype system that implements a multi-modal interface for control of the television. This system combines the standard TV remote control with a dialog management based natural language speech interface to allow users to efficiently interact with the TV, and to seamlessly alternate between the two modalities. One of the main objectives of this system is to make the unwieldy Electronic Program Guide information more navigable by the use of voice to filter and locate programs of interest.
A Chebyshev spectral collocation method for solving Burgers'-type equations
Authors: A. H. Khater, R. S. Temsah, M. M. Hassan
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper, we elaborated a spectral collocation method based on differentiated Chebyshev polynomials to obtain numerical solutions for some different kinds of nonlinear partial differential equations. The problem is reduced to a system of ordinary differential equations that are solved by Runge-Kutta method of order four. Numerical results for the nonlinear evolution equations such as 1D Burgers', KdV-Burgers', coupled Burgers', 2D Burgers' and system of 2D Burgers' equations are obtained. The numerical results are found to be in good agreement with the exact solutions. Numerical computations for a wide range of values of Reynolds' number, show that the present method offers better accuracy in comparison with other previous methods. Moreover the method can be applied to a wide class of nonlinear partial differential equations.