ppxscal/embedding_network huggingface dataset:
The design of fuzzy information granules: Tradeoffs between specificity and experimental evidence
Authors: Fusheng Yu, Witold Pedrycz
Venue: Applied Soft Computing (2009)

Granulation of information has become an underlying concept permeating a vast array of pursuits. In this study, we address a fundamental issue of the design of ''meaningful'' information granules. The underlying principle guiding their development realizes a tradeoff between a specificity of information granule (which we want to keep as high as possible) and the associated experimental evidence (which needs to be maintained high as well). Recognizing the fact that these are directly in conflict, we formulate the problem as a certain optimization task. In the sequel, we discuss the solutions and analyze their properties. In particular, we will deal with an array of parametric optimization dealing with various commonly encountered types of membership functions.
Improved network-based identification of protein orthologs
Authors: Nir Yosef, Roded Sharan, William Stafford Noble
Venue: Bioinformatics (2008)

Motivation: Identifying protein orthologs is an important task that is receiving growing attention in the bioinformatics literature. Orthology detection provides a fundamental tool towards understanding protein evolution, predicting protein functions and interactions, aligning protein–protein interaction (PPI) networks of different species and detecting conserved modules within these networks. Results: Here, we present a novel diffusion-based framework that builds on the Rankprop algorithm for protein orthology detection and enhances it in several important ways. Specifically, we enhance the Rankprop algorithm to account for the presence of multiple paralogs, utilize PPI, and consider multiple (>2) species in parallel. We comprehensively benchmarked our framework using a variety of training datasets and experimental settings. The results, based on the yeast, fly and human proteomes, show that the novel enhancements of Rankprop provide substantial improvements over its original formulation as well as over a number of state of the art methods for network-based orthology detection. Availability: datasets and source code are available upon request. Contact: niryosef@post.tau.ac.il
Tree exploration with advice
Authors: Pierre Fraigniaud, David Ilcinkas, Andrzej Pelc
Venue: Information and Computation (2008)

We study the amount of knowledge about the network that is required in order to efficiently solve a task concerning this network. The impact of available information on the efficiency of solving network problems, such as communication or exploration, has been investigated before but assumptions concerned availability of particular items of information about the network, such as the size, the diameter, or a map of the network. In contrast, our approach is quantitative: we investigate the minimum number of bits of information (bits of advice) that has to be given to an algorithm in order to perform a task with given efficiency. We illustrate this quantitative approach to available knowledge by the task of tree exploration. A mobile entity (robot) has to traverse all edges of an unknown tree, using as few edge traversals as possible. The quality of an exploration algorithm A is measured by its competitive ratio, i.e., by comparing its cost (number of edge traversals) to the length of the shortest path containing all edges of the tree. Depth-First-Search has competitive ratio 2 and, in the absence of any information about the tree, no algorithm can beat this value. We determine the minimum number of bits of advice that has to be given to an exploration algorithm in order to achieve competitive ratio strictly smaller than 2. Our main result establishes an exact threshold number of bits of advice that turns out to be roughly loglogD, where D is the diameter of the tree. More precisely, for any constant c, we construct an exploration algorithm with competitive ratio smaller than 2, using at most loglogD-c bits of advice, and we show that every algorithm using loglogD-g(D) bits of advice, for any function g unbounded from above, has competitive ratio at least 2.
Stochastic learning solution for distributed discrete power control game in wireless data networks
Authors: Yiping Xing, R. Chandramouli
Venue: IEEE/ACM Transactions on Networking (TON) (2008)

Distributed power control is an important issue in wireless networks. Recently, noncooperative game theory has been applied to investigate interesting solutions to this problem. The majority of these studies assumes that the transmitter power level can take values in a continuous domain. However, recent trends such as the GSM standard and Qualcomm's proposal to the IS-95 standard use a finite number of discretized power levels. This motivates the need to investigate solutions for distributed discrete power control which is the primary objective of this paper. We first note that, by simply discretizing, the previously proposed continuous power adaptation techniques will not suffice. This is because a simple discretization does not guarantee convergence and uniqueness. We propose two probabilistic power adaptation algorithms and analyze their theoretical properties along with the numerical behavior. The distributed discrete power control problem is formulated as an N-person, nonzero sum game. In this game, each user evaluates a power strategy by computing a utility value. This evaluation is performed using a stochastic iterative procedures. We approximate the discrete power control iterations by an equivalent ordinary differential equation to prove that the proposed stochastic learning power control algorithm converges to a stable Nash equilibrium. Conditions when more than one stable Nash equilibrium or even only mixed equilibrium may exist are also studied. Experimental results are presented for several cases and compared with the continuous power level adaptation solutions.
Evita raced: metacompilation for declarative networks
Authors: Tyson Condie, David Chu, Joseph M. Hellerstein, Petros Maniatis
Venue: Proceedings of the VLDB Endowment (2008)

Declarative languages have recently been proposed for many new applications outside of traditional data management. Since these are relatively early research efforts, it is important that the architectures of these declarative systems be extensible, in order to accommodate unforeseen needs in these new domains. In this paper, we apply the lessons of declarative systems to the internals of a declarative engine. Specifically, we describe our design and implementation of Evita Raced, an extensible compiler for the OverLog language used in our declarative networking system, P2. Evita Raced is a metacompiler: an OverLog compiler written in OverLog. We describe the minimalist architecture of Evita Raced, including its extensibility interfaces and its reuse of P2's data model and runtime engine. We demonstrate that a declarative language like OverLog is well-suited to expressing traditional and novel query optimizations as well as other query manipulations, in a compact and natural fashion. Finally, we present initial results of Evita Raced extended with various optimization programs, running on both Internet overlay networks and wireless sensor networks.
Ionic outgassing from photoacid generators upon irradiation at 13.5nm
Authors: Grace H. Ho, Chih-Jen Liu, Chih-Han Yen, Ming-Hsuan Ho, Sih-Yu Wu
Venue: Microelectronic Engineering (2008)

Photoresist outgassing is considered a possible source of contamination of optics in extreme ultraviolet (EUV) lithography at 13.5nm. We measured the relative proportions of ionic outgassing from 18 commercially available photoacid generators (PAG), which is a key component of chemically amplified photoresists, upon irradiation at 13.5nm. These PAG include 17 triarylsulfonium or diaryliodonium salts, which contain CF"3SO"3^- or C"4F"9SO"3^- as the anion, and one PAG of molecular type. The overall outgassed ions in the range 10-200u were counted in relative proportions. Outgassing of F^+ is found to be dominant, and for most PAG the extent of F^+ outgassing shows a satisfactory correlation with the ratio of F atomic photoabsorption to the overall PAG photoabsorption. Outgassed ions F^+, CF^+, CF"2^+ and CF"3^+ from PAG containing the CF"3SO"3^- anion and additional C"xF"y^+ such as C"2F"4^+, C"2F"5^+ and C"3F"5^+ from those containing C"4F"9SO"3^- are identified. Triphenylsulfonium perfluoro-1-butanesulfonate is one PAG to emit the most abundant F^+ and total ionic fragments, and a PAG of molecular type (N-hydroxy-5-norbornene-2,3-dicarboximide perfluoro-1-butanesulfonate) also emits abundantly both hydrocarbon ions and F^+. Ionic outgassing of PAG cations includes (C"6H"5)"2S^+ from R(C"6H"5)"2S^+ salts and I^+ from diaryliodonium salts. For PAG containing t-C"4H"9, significantly less F^+ outgassing is observed; additional outgassing pathways are proposed. The pressure rise caused by PAG shows no dependence on the anion identity, but is correlated with cation photoabsorption, and ascribed to neutral aryl outgassing. Other minor outgassing species include HSO"2^+ from sulfonates; C"1"1H"9^+ and 'photostable' PAH cations C"1"2H"8^+ are identified for the first time and provide evidence of concurrent outgassing from, and polymerization of, PAG upon irradiation at 13.5nm.
Predicting financial activity with evolutionary fuzzy case-based reasoning
Authors: Sheng-Tun Li, Hei-Fong Ho
Venue: Expert Systems with Applications: An International Journal (2009)

Predicting financial activity through examining the short-term liquidity is crucial within today's turbulent financial environment. Firms, governments, and individuals all need an effective methodology based on liquidity information that plays performance deterioration warning a priori bankruptcy prediction. In this paper, we propose a hybrid decision model using case-based reasoning augmented with genetic algorithms (GAs) and the fuzzy k nearest neighbor (fuzzy k-NN) methods for predicting the financial activity rate. GAs are used to determine the optimal or near-optimal weight vector of financial features expressed in linguistic values by the expert. A fuzzy k-NN-based CBR scheme is designed to compute memberships of financial activity rates and to provide a more flexible and practical mechanism for acquiring, creating, and reusing the expert's decision knowledge. An empirical experimentation using 746 publicly traded Taiwanese firms shows that the average accuracy of the rating is about 92.36%, which is superior to other related models. The proposed approach not only can lend support to the decision of an expert, but also allow proper feedback for the expert to improve the quality of the decision.
Mixed Discontinuous Galerkin Finite Element Method for the Biharmonic Equation
Authors: Thirupathi Gudi, Neela Nataraj, Amiya K. Pani
Venue: Journal of Scientific Computing (2008)

In this paper, we first split the biharmonic equation Δ2 u=f with nonhomogeneous essential boundary conditions into a system of two second order equations by introducing an auxiliary variable v=Δu and then apply an hp-mixed discontinuous Galerkin method to the resulting system. The unknown approximation v h of v can easily be eliminated to reduce the discrete problem to a Schur complement system in u h , which is an approximation of u. A direct approximation v h of v can be obtained from the approximation u h of u. Using piecewise polynomials of degree p¿3, a priori error estimates of u¿u h in the broken H 1 norm as well as in L 2 norm which are optimal in h and suboptimal in p are derived. Moreover, a priori error bound for v¿v h in L 2 norm which is suboptimal in h and p is also discussed. When p=2, the preset method also converges, but with suboptimal convergence rate. Finally, numerical experiments are presented to illustrate the theoretical results.
The Influence of Control on the Acceptance of Ambient Intelligence by Elderly People: An Explorative Study
Authors: Lambert Zaad, Somaya Ben Allouch
Venue: Proceedings of the European Conference on Ambient Intelligence (2008)

This paper presents the results of a study on how elderly people perceive an intelligent system, embedded in their home, which should enable them to live independently longer. Users of a motion sensor system were interviewed about their experiences. A sensor system that autonomously works as well as a manipulated version was studied. The manipulation contained a touch screen that informed the users if the gathered information was correct before sending it to caregivers, so more control over personal information was provided. To test the use intention of the motion sensor system Spiekermann's Ubiquitous Computing Acceptance Model of was used. This study shows that people, who perceive more control over their wellbeing, show more use intention. And that the subjective norm influences their acceptance. This study shows that acceptance models for Ambient Intelligence application in care situations need to be developed.
A Method for Integration across Text Corpus and WordNet-Based Ontologies
Authors: Trong Hai Duong, Geun Sik Jo, Ngoc Thanh Nguyen
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 (2008)

Most information in the world exists in the format of text, such as news articles and web pages. Different lines of research have been conducted to discover, understand and access knowledge about real-world entities and relations from text. However, the application of these word oriented methods to ontology integration tasks has not been yet explored. In this paper, we apply these word oriented methods to ontology integration tasks in which we analyze a noun phrase (NP) to identify its head noun, which is useful to avoid wrong relations between entities. We also propose a collaborative acquisition algorithm that combines WordNet-based and Text corpus.
Analysis of a class of easily computable permutations
Authors: V. G. Skobelev, E. Ye. Zaitseva
Venue: Cybernetics and Systems Analysis (2008)

Properties of easily computable permutations specified in terms of a finite ring are investigated. It is established that problems of parametric identification for this class of permutations are reduced to the resolution of systems of Diophantine equations of sufficiently high degree and to the solution of systems of problems of taking discrete logarithms.
Collaborative Environment for Engineering Simulations with Integrated VR Visualization
Authors: Ismael H. Santos, Alberto B. Raposo, Marcelo Gattass
Venue: Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS (2008)

We present an SOA for executing engineering simulations and visualizing results in a Virtual Environment. Different technologies of group work are used to compose a Collaborative Problem Solving Environment that enables engineers to setup computations in an integrated environment.
Mark-and-sweep: getting the "inside" scoop on neighborhood networks
Authors: Dongsu Han, Aditiya Agarwala, David G. Andersen, Michael Kaminsky, Konstantina Papagiannaki, Srinivasan Seshan
Venue: Proceedings of the 8th ACM SIGCOMM conference on Internet measurement (2008)

Residential Internet connectivity is growing at a phenomenal rate. A number of recent studies have attempted to characterize this connectivity - measuring coverage and performance of last-mile broadband links - from a various vantage points on the Internet, via wireless APs, and even with user cooperation. These studies, however, sacrifice accuracy or require substantial human time. In this work, we present a novel two-pass method to characterize neighborhood networks. We demonstrate that the two pass method dramatically reduces the time spent in active measurement while retaining accuracy. A case study on two neighborhoods in Pittsburgh provide new and accurate insights into broadband connectivity, including throughput, broadband coverage (DSL vs. cable vs. fiber), NAT configurations, DHCP, DNS usage. The results further characterize 802.11 connectivity in the neighborhood.
Substitute valuations: Generation and structure
Authors: Bruce Hajek
Venue: Performance Evaluation (2008)

Substitute valuations (in some contexts called gross substitute valuations) are prominent in combinatorial auction theory. An algorithm is given in this paper for generating a substitute valuation using a random number generator. In addition, the geometry of the set of all substitute valuations for a fixed number of goods K is investigated. The set consists of a union of polyhedrons, and the maximal polyhedrons are identified for K=4. It is shown that the maximum dimension of the polyhedrons increases with K nearly as fast as two to the power K. Consequently, under broad conditions, if a combinatorial algorithm can present an arbitrary substitute valuation given a list of input numbers, the list must grow nearly as fast as two to the power K.
Improving Multi-agent Evolutionary Techniques with Local Search for Job Shop Scheduling Problem
Authors: Ahmad Balid, Sonajharia Minz
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

Scheduling is the allocation of shared resources over time in order to perform a number of tasks. Job Shop Scheduling Problem (JSSP) is the most commonly encountered scheduling problem. A wide range of approaches have been proposed to solve it. In this paper two multi-agent based evolutionary models are proposed to tackle JSSP. The first one is Multi-Agent based Genetic Algorithm (MAGA) and the second model is a Multi-Agent Particle Swarm Optimization (MAPSO). A proposed local search technique as self-learning procedure for agents is hybridized with both of the multi-agent models to enhance their efficiency. The proposed models have been implemented using REPAST toolkit. Encouraging results from both models have been obtained for standard benchmarks from OR library.
Bayesian belief network for box-office performance: A case study on Korean movies
Authors: Kyung Jae Lee, Woojin Chang
Venue: Expert Systems with Applications: An International Journal (2009)

Due to their definition as experience goods with short product lifetime cycles, it is difficult to forecast the demand for motion pictures. Nevertheless, producers and distributors of new movies need to forecast box-office results in an attempt to reduce the uncertainty in the motion picture business. Previous research demonstrated the ability of certain movie attributes such as early box-office data and release season to forecast box-office revenues. However, no previous research has focused on the causal relationship among various movie attributes, which have the potential to increase the accuracy of box-office predictions. In this paper a Bayesian belief network (BBN), which is known as a causal belief network, is constructed to investigate the causal relationship among various movie attributes in the performance prediction of box-office success. Subsequently, sensitivity analysis is conducted to determine those attributes most critically related to box-office performance. Finally, the probability of a movie's box-office success is computed using the BBN model based on the domain knowledge from the value chain of theoretical motion pictures. The results confirm the improved forecasting accuracy of the BBN model compared to artificial neural network and decision tree.
Child head injury criteria investigation through numerical simulation of real world trauma
Authors: Sebastien Roth, Jonathan Vappou, Jean-Sebastien Raul, Rémy Willinger
Venue: Computer Methods and Programs in Biomedicine (2009)

Finite element modelling has been used for decades in the study of adult head injury biomechanics and determination of injury criteria. Interest is recently growing in investigation on pediatric head injury which requires elaboration of biofidelic models that take into account child's head particularities in terms of size, geometry, and mechanical properties. In this study, a finite element model of a 3-year-old child head is proposed. The model is reconstructed from real CT scan images and mechanical properties are extracted from available data in the literature. A large number of real accidents (25 falls) are reconstructed with proposed model using different brain constitutive relationships in order to investigate their influence on model response. Mechanical output parameters (HIC, pressure, shearing stress) are calculated from these simulations. Statistical analysis was performed in order to evaluate predictive capability of the parameters. Von Mises stress appears to be clearly the most predictive parameters, allowing clear distinction between injured and non-injured cases. To the authors' knowledge, this study proposes for the first time a statistically based neurological injury criterion for a pediatric population using finite element modelling.
MotifVoter
Authors: Edward Wijaya, Siu-Ming Yiu, Ngo Thanh Son, Rajaraman Kanagasabai, Wing-Kin Sung
Venue: Bioinformatics (2008)

Motivation: Locating transcription factor binding sites (motifs) is a key step in understanding gene regulation. Based on Tompa's benchmark study, the performance of current de novo motif finders is far from satisfactory (with sensitivity ≤0.222 and precision ≤0.307). The same study also shows that no motif finder performs consistently well over all datasets. Hence, it is not clear which finder one should use for a given dataset. To address this issue, a class of algorithms called ensemble methods have been proposed. Though the existing ensemble methods overall perform better than stand-alone motif finders, the improvement gained is not substantial. Our study reveals that these methods do not fully exploit the information obtained from the results of individual finders, resulting in minor improvement in sensitivity and poor precision. Results: In this article, we identify several key observations on how to utilize the results from individual finders and design a novel ensemble method, MotifVoter, to predict the motifs and binding sites. Evaluations on 186 datasets show that MotifVoter can locate more than 95% of the binding sites found by its component motif finders. In terms of sensitivity and precision, MotifVoter outperforms stand-alone motif finders and ensemble methods significantly on Tompa's benchmark, Escherichia coli, and ChIP-Chip datasets. MotifVoter is available online via a web server with several biologist-friendly features. Availability: http://www.comp.nus.edu.sg/~bioinfo/MotifVoter Contact: ksung@comp.nus.edu.sg supplementary information:Supplementary data are available at Bioinformatics online.