ppxscal/embedding_network huggingface dataset:
Algorithms on clustering, orienteering, and conflict-free coloring
Authors: Sariel Har-Peled
Venue:  (2007)

We present algorithms for three geometric problems&mdash;clustering, orienteering, and conflict-free coloring. In the first part, we obtain small coresets for k-median and k-means clustering in general metric spaces and in Euclidean spaces. In Rd , these coresets have size that depend polynomially on d. This leads to more efficient approximation algorithms for k-median and k-means clustering. We use those coresets to maintain a (1 + &egr;)-approximate k-median and k-means clustering of a stream of points in Rd , using O(dk2 &egr;-2 log8 n) space. These are the first streaming algorithms, for those problems, that have space complexity with polynomial dependency on the dimension. We next study the k-median clustering with outliers problem. Here, given a finite point set in a metric space and parameters k and m, we want to remove m points (called outliers), such that the cost of the optimal k-median clustering of the remaining points is minimized. We present the first polynomial time constant factor approximation algorithm for this problem. In the second part, we consider the rooted orienteering problem: Given a set P of n points in the plane, a starting point r &isin; P, and a length constraint B, one needs to find a path starting from r that visits as many points of P as possible and of length not exceeding B. We present the first polynomial time approximation scheme (PTAS) for this problem. The scheme also works in higher (fixed) dimensions. In the last part, we present randomized algorithms for online conflict-free coloring of points in the plane, with respect to intervals, halfplanes, congruent disks, and nearly-equal axis-parallel rectangles. In all these cases, the coloring algorithms use O(log n) colors, with high probability. We also present the first efficient deterministic algorithm for the CF coloring of points in the plane with respect to nearly-equal axis-parallel rectangles, using O(log 12 n) colors.
Bioinformatics' Challenges to Computer Science
Authors: Mario Cannataro, Mathilde Romberg, Joakim Sundnes, Rodrigo Weber Dos Santos
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

The workshop Bioinformatics' Challenges to Computer Science covers the topics of data management and integration, modelling and simulation of biological systems and data visualization and image processing. This short paper describes the requirements Bioinformatics has towards computer science, summarizes the papers accepted for the workshop and gives a brief outlook on future developments.
Research on Application of Improved Association Rules Algorithm in Intelligent QA System
Authors: Youfu Du, Ming Zhao, Guanjun Fan
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

With increasingly prevalent of E-learning, the intelligent Q/A system arise at the historic moment. In this paper we proposed an improved text cluster algorithm, with the improved association rules algorithm, it can classify the information in the database accurately according to the questions, locate the user's question fast and therefore speeds up the inquiry rate. The experimental result indicates that this plan has the merits of intelligence, self-renewing, and efficient Q/A and so on.
On Computing the Underlying Fiber Directions from the Diffusion Orientation Distribution Function
Authors: Luke Bloy, Ragini Verma
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

In this work, a novel method for determining the principal directions (maxima) of the diffusion orientation distribution function(ODF) is proposed. We represent the ODF as a symmetric high-order Cartesian tensor restricted to the unit sphere and show that the extrema of the ODF are solutions to a system of polynomial equations whose coefficients are polynomial functions of the tensor elements. In addition to demonstrating the ability of our methods to identify the principal directions in real data, we show that this method correctly identifies the principal directions under a range of noise levels. We also propose the use of the principal curvatures of the graph of the ODF function as a measure of the degree of diffusion anisotropy in that direction. We present simulated results illustrating the relationship between the mean principal curvature, measured at the maxima, and the fractional anisotropy of the underlying diffusion tensor.
Plenary lecture VIII: toward physics of the mind: concepts, emotions, consciousness, and symbols
Authors: Leonid Perlovsky
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

Recent advances in mathematics, cognitive science, and neurobiology are bringing us close to physical theory of the mind. We can describe mathematically concepts, emotions, instincts, imaginations, intuitions. All of these are inseparable from perception and cognition. These, in turn, are related to inverse scattering: we infer properties of the world from scattered light and sound waves. I first explain a scheme for reducing combinatorial complexity often encountered in the past attempts at designing "intelligent systems," and then briefly discuss engineering applications (data mining, fusion, financial predictions, Internet search engines); and present results demonstrating orders of magnitude improvement in classical detection and tracking in noise. The last part of the talk moves to future research directions: roles of the beautiful, music, sublime in the mind, cognition, consciousness, and evolution. The current "East vs. West" confrontation turns out related to differences in grammar between English and Arabic. What are the mechanisms of language and cultural evolution? Presented mathematical theory is related to the knowledge instinct, which drives the mind to understand the world. This instinct is even more important than sex or food. This connects computers and the mind, the high and the mundane.
Ontology for Enterprise Modeling
Authors: Ronald L. Hartung, Jay Ramanathan, Joe Bolinger
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

Enterprise modeling has a history of related research that has advanced high-level concepts that do not map well to implementation-oriented models like UML. Here acknowledging that the enterprise and business context impacts implementation requirements for adaptive services, we introduce the notation for representing the Adaptive Complex Enterprises through the Requirements-Execution-Delivery interaction or primitive. This simple primitive allows complex models to be developed that treats business processes at all levels and underlying data processing systems as well as human processing systems in a holistic fashion. In this paper we introduce the ontology underlying the Requirements-Execution-Delivery interactions, thus allowing Requirements-Execution-Delivery to be precisely specified as a single primitive for modeling, execution, and monitoring the behavior of Adaptive Complex Enterprises. We show how this takes the concepts developed in artificial intelligence and applies it into business activity monitoring.
An Alternative to Center-Based Clustering Algorithm Via Statistical Learning Analysis
Authors: Rui Nian, Guangrong Ji, Michel Verleysen
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

This paper presents an alternative for center-based clustering algorithms, in particular the k-means algorithm, via statistical learning analysis. The essence of statistical learning principle, i.e., both the empirical risk and structural assessment, is taken into particular consideration for the clustering algorithm so as to derive and develop the relevant minimization mathematical criterion with automatic parameter learning and model selection in parallel. The proposed algorithm roughly decides on the number of clusters, by earning activation for the winners and assigning penalty for the rivals, so that the most competitive center wins for possible prediction and the extra ones are driven far away when starting the algorithm from a too large number of clusters without any prior knowledge. Simulation experiments prove the feasibility of the algorithm and show good performances of the double learning tasks during clustering.
Influential Factors on Incident Management: Lessons Learned from a Large Sample of Products in Operation
Authors: João Caldeira, Fernando Brito E Abreu
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

Understanding causal relationships on incident management can help software development organizations in finding the adequate level of resourcing, as well as improving the quality of services they provide to their end-users and/or cus tomers. This paper presents an empirical study conducted upon a sample of in cident reports recorded during the operation of several hundred commercial software products, over a period of three years, on six countries in Europe and Latin America. The underlying research questions refer to the validation of which are the influencing factors affecting the incidents management lifecycle. Non parametric analysis of variance procedures are used for testing hypotheses.
Spectral structure of the equilateral triangle II: beyond Lamé's formulas
Authors: Brian J. McCartin
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

The extension of Lamé's formulas for the eigenvalues and eigenfunctions of the Laplacian on an equilateral triangle to the Robin problem with a radiation/absorbing boundary condition is reviewed. The eigenfunctions are shown to form a complete orthogonal system. Various properties of the spectrum and modal functions are explored.
Ab Initio and DFT Investigations of the Mechanistic Pathway of Singlet Bromocarbenes Insertion into C-H Bonds of Methane and Ethane
Authors: M. Ramalingam, K. Ramasami, P. Venuvanalingam, J. Swaminathan
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

The mechanistic pathway of singlet bromocarbenes (1CHBr and 1CBr2) insertions into the C-H bonds of methane and ethane have been analysed at ab initio (HF and MP2) and DFT (B3LYP) level of theories using 6-31g (d, p) basis set. The QCISD//MP2/6-31g(d, p) level predicts higher activation barriers. NPA, Mulliken and ESP charge analyses have been carried out along the minimal reaction path by the IRC method at B3LYP and MP2 levels for these reactions. The occurrence of the TSs either in the electrophilic or nucleophilic phase and net charge flow from alkane to carbene in the TS has been identified through NBO analyses.
Developing an embedded gyroscope sensor with kalman filter noise reducing algorithm for mobile robot
Authors: Saeed Ebrahimijam, Mahdi Yousefi Azarkhanian, Hamed Rasam Fard, Sepehr Moein
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

This paper introduces the result of developing an embedded gyroscope sensor for mobile robot to calculate the rotational movements. By adding an adaptive kalman filter, the output data of the sensor became more accurate and noiseless. According to the experiments results, by developing such system the error of the measurement decreased to less than ± 5° in ±180° rotation which is appropriate for our application. The system is implemented and tested on MRL (Mechatronics Research Laboratory) middle size soccer robot to prove the efficiency and reliability for substitution with odometric sensors like optical encoders of the robot [1], also the data of the sensor is feed to the vision sensor for matching in the localization.
Module-Based Modeling of Cyber-Physical Power Systems
Authors: Le Xie, Marija D. Ilic
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

In this paper we present a module-based modeling of electrical power grids. Each (group of) component(s) is defined as a module and its dynamics is represented in terms of its local variables and the interconnection variables between the module and the system network. Therefore, it is possible to specify the performance sub-objectives of each module for a given range of variations in interaction variables and to ensure that the local sub-objectives are met through local sensing and actuation. The specifications are implemented through an interactive cyber-based protocol between the local modules and the network operator. The network operator defines bounds on the interaction variables. Individual modules, in turn, adjust their own localcontrol to meet local performance specifications for the given bounds on the interaction variables. Sufficient conditions on network properties are derived under which this interactive protocol between the network operation and themodules converges to a system-wide stable operation. The proposed interactive protocol could be used for incorporating into future electric power grids high penetration of distributed generation resources, and this is illustrated on a simple example.
Overview of INEX 2007 Link the Wiki Track
Authors: Darren Wei Huang, Yue Xu, Andrew Trotman, Shlomo Geva
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

Wikipedia is becoming ever more popular. Linking between documents is typically provided in similar environments in order to achieve collaborative knowledge sharing. However, this functionality in Wikipedia is not integrated into the document creation process and the quality of automatically generated links has never been quantified. The Link the Wiki (LTW) track at INEX in 2007 aimed at producing a standard procedure, metrics and a discussion forum for the evaluation of link discovery. The tasks offered by the LTW track as well as its evaluation present considerable research challenges. This paper briefly described the LTW task and the procedure of evaluation used at LTW track in 2007. Automated link discovery methods used by participants are outlined. An overview of the evaluation results is concisely presented and further experiments are reported.
Uniquely Represented Data Structures for Computational Geometry
Authors: Guy E. Blelloch, Daniel Golovin, Virginia Vassilevska
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

We present new techniques for the construction of uniquely represented data structures in a RAM, and use them to construct efficient uniquely represented data structures for orthogonal range queries, line intersection tests, point location, and 2-D dynamic convex hull. Uniquely represented data structures represent each logical state with a unique machine state. Such data structures are strongly history-independent. This eliminates the possibility of privacy violations caused by the leakage of information about the historical use of the data structure. Uniquely represented data structures may also simplify the debugging of complex parallel computations, by ensuring that two runs of a program that reach the same logical state reach the same physical state, even if various parallel processes executed in different orders during the two runs.
Particle swarm optimization technique based short-term hydrothermal scheduling
Authors: K. K. Mandal, M. Basu, N. Chakraborty
Venue: Applied Soft Computing (2008)

Particle swarm optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal power system. A multi-reservoir cascaded hydroelectric system with a nonlinear relationship between water discharge rate, net head and power generation is considered. The water transport delay between connected reservoirs is taken into account. In the present work, the effects of valve point loading in the fuel cost function of the thermal plants are also taken into consideration. The developed algorithm is illustrated for a test system consisting of four hydro plants and three thermal plants. Cost characteristics of individual thermal units are considered. The test results are compared with those obtained using evolutionary programming and simulated annealing technique. It is found that the convergence characteristic is excellent and the results obtained by the proposed method are superior in terms of fuel cost and computation time.
Multistage RBF neural network ensemble learning for exchange rates forecasting
Authors: Lean Yu, Kin Keung Lai, Shouyang Wang
Venue: Neurocomputing (2008)

In this study, a multistage nonlinear radial basis function (RBF) neural network ensemble forecasting model is proposed for foreign exchanger rates prediction. In the process of ensemble modeling, the first stage produces a great number of single RBF neural network models. In the second stage, a conditional generalized variance (CGV) minimization method is used to choose the appropriate ensemble members. In the final stage, another RBF network is used for neural network ensemble for prediction purpose. For testing purposes, we compare the new ensemble model's performance with some existing neural network ensemble approaches in terms of four exchange rates series. Experimental results reveal that the predictions using the proposed approach are consistently better than those obtained using the other methods presented in this study in terms of the same measurements.
A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains
Authors: Rocío Alaiz-Rodríguez, Nathalie Japkowicz, Peter Tischer
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

Classifier performance evaluation typically gives rise to a multitude of results that are difficult to interpret. On the one hand, a variety of different performance metrics can be applied, each adding a little bit more information about the classifiers than the others; and on the other hand, evaluation must be conducted on multiple domains to get a clear view of the classifier's general behaviour.
Reasoning with Uncertainty by Nmatrix---Metric Semantics
Authors: Ofer Arieli, Anna Zamansky
Venue: Proceedings of the 15th international workshop on Logic, Language, Information and Computation (2008)

Non-deterministic matrices, a natural generalization of many-valued matrices, are semantic structures in which the value assigned to a complex formula may be chosen non-deterministically from a given set of options. We show that by combining Nmatrices and preferential metric-based considerations, one obtains a family of logics that are useful for reasoning with uncertainty. We investigate the basic properties of these logics and demonstrate their usefulness in handling incomplete and inconsistent information.
Tuning Quantum Multi-Swarm Optimization for Dynamic Tasks
Authors: Krzysztof Trojanowski
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

Heuristic approaches already proved their efficiency for the cases where real-world problems dynamically change in time and there is no effective way of prediction of the changes. Among them a mixed multi-swarm optimization (mSO) is regarded as the most efficient. The approach is a hybrid solution and it is based on two types of particle swarm optimization (PSO): pure PSO and quantum swarm optimization (QSO). Both types are applied in a set of simultaneously working sub-swarms. In spite of the fact that there appeared a series of publications discussing properties of this approach the motion mechanism of quantum particles was just briefly studied, and there is still some research to do. This paper presents the results of our research on this subject. The novelty is based on a new type of distributions of particles in a quantum cloud. Obtained results allow to derive some guidelines of an effective tuning of the mechanism of distribution in the quantum cloud and show that further improvement of mSO is possible.
Canonical Inference for Implicational Systems
Authors: Maria Paola Bonacina, Nachum Dershowitz
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

Completion is a general paradigm for applying inferences to generate a canonical presentation of a logical theory, or to semi-decide the validity of theorems, or to answer queries. We investigate what canonicity means for implicational systems that are axiomatizations of Moore families --- or, equivalently, of propositional Horn theories. We build a correspondence between implicational systems and associative-commutative rewrite systems, give deduction mechanisms for both, and show how their respective inferences correspond. Thus, we exhibit completion procedures designed to generate canonical systems that are "optimal" for forward chaining, to compute minimal models, and to generate canonical systems that are rewrite-optimal. Rewrite-optimality is a new notion of "optimality" for implicational systems, one that takes contraction by simplification into account.
A Differential Power Analysis Attack of Block Cipher Based on the Hamming Weight of Internal Operation Unit
Authors: Jeahoon Park, Hoonjae Lee, Jaecheol Ha, Yongje Choi, Howon Kim, Sangjae Moon
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

Power analysis attack, which was introduced by Kocher et al. in 1999, was known as the most threatening physical attack against low power device such as smart-card. The essential reason that allows an attacker to implement a power analysis attack on a cryptosystem is leakage information, which is leaked during the operation of the cryptosystem¿s encryption/decryption process and related to internal secret information. The general and efficient power analysis attack method proposed in this paper is based on an internally divided operation unit. As such, the proposed power analysis attack is implemented to expose the weakness of the operation of a symmetric key encryption algorithm in a smart-card.
Is Random Scheduling Sufficient in P2P Video Streaming?
Authors: Chao Liang, Yang Guo, Yong Liu
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Peer-to-Peer (P2P) technology has recently been employed to deliver large scale video multicast services on the Internet. Considerable efforts have been made by both academia and industry on P2P streaming design. While academia mostly focus on exploring design space to approach the theoretical performance bounds, our recent measurement study on several commercial P2P streaming systems indicates that they are able to deliver good user Quality of Experience with seemingly simple designs. One intriguing question remains: how elaborate should a good P2P video streaming design be? Towards answering this question, we developed and implemented several representative P2P streaming designs, ranging from theoretically proved optimal designs to straight forward "naive" designs. Through an extensive comparison study on PlanetLab, we unveil several key factors contributing to the successes of simple P2P streaming designs, including system resource index, sever capacity and chunk scheduling rule, peer download buffering and peering degree. We also identify regions where naive designs are inadequate and more elaborate designs can improve things considerably. Our study not only brings us better understandings and more insights into the operation of existing systems, it also sheds lights on the design of future systems that can achieve a good balance between the performance and the complexity.