ppxscal/embedding_network huggingface dataset:
Perspectives and challenges of agent-based simulation as a tool for economics and other social sciences
Authors: Klaus G. Troitzsch
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

This paper argues that the agent-based simulation approach is just the one appropriate to the social sciences (including economics). Although there were many predecessor approaches, which tried to build formal models of social systems, all of them fell short of the peculiar features of the objects of all social sciences: complex systems consisting of numerous autonomous actors who interact with each other, who take on different roles at the same time, who are conscious of their interactions and roles and who can communicate with the help of symbolic languages even about the counterfactual. These human actors are unlike physical particles although their behaviour might sometimes be quite similar to the behaviour of physical particles when humans occur in very large numbers (but they are most interesting when they form only small networks). Real human actors would not concede that their behaviour is stochastic, they will always assert that their actions are deliberate (but at the same time these actions are not entirely predictable). Human actors are not entirely rational although their behaviour might sometimes seem as if they were (but they are most interesting when their rationality is only bounded and when their payoff is multidimensional). Social systems seem to be the most adaptive systems that we know about, and this is why we could perhaps use them as patterns for artificial adaptive systems --- and if we knew enough about the modes of operations of human social systems, social sciences could even contribute to agent-based modelling in other fields.
From GENIA to BIOTOPTowards a Top-Level Ontology for Biology
Authors: Stefan Schulz, Elena Beisswanger, Udo Hahn, Joachim Wermter, Anand Kumar, Holger Stenzhorn
Venue: Proceeding of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006) (2006)

The increasing need for advanced ontology-based knowledge management in the life sciences is generally being acknowledged but, up until now, the development of biological ontologies lacks adherence to foundational principles of ontology design. This is particularly true of so-called upper-level ontologies such as the GENIA ontology which covers biological continuants and has mainly been devised for corpus annotation in a text mining context. As an alternative, we introduce BIOTOP,an upper ontology of physical continuants in the domain of biology, with a coverage similar to the GENIA ontology. We report on design specifications and modeling decisions for BIOTOP which are based upon formal ontology principles. As a major desideratum, these continuants are described in terms of necessary and sufficient conditions. We accomplished this goal for 85 out of the 146 existing GENIA classes. We use OWL-DL as a formal knowledge representation language and may thus use a terminological reasoner for classification in order to check and maintain consistency during the ontology engineering phase.
An energy-based vehicle tracking system using principal component analysis and unsupervised ART network
Authors: A. Srikaew, P. Kumsawat, K. Attakitmongcol, N. Sroisuwan, C. Sotthithaworn
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

This work presents an automatic vehicle detecting and tracking system from a sequence of images. The vehicle detection system uses energy-based images including symmetry energy, Gabor energy, and road energy, to initially locate vehicles in each image. The tracking system then utilizes the adaptive resonance theory network for vehicle recognition and tracking based on vehicle energy images. The vehicle energy images are fed into the network which can automatically recognize salient features of vehicles by analyzing theirs principal components. This unsupervised network allows the system to efficiently perform tracking in dynamic environments where shapes and sizes of vehicles are changing all the time. By using the vehicle energy model, the proposed system can also track multiple vehicles simultaneously, both frontal and rear view. Results and discussions are described.
Propagation via lazy clause generation
Authors: Olga Ohrimenko, Peter J. Stuckey, Michael Codish
Venue: Constraints (2009)

Finite domain propagation solvers effectively represent the possible values of variables by a set of choices which can be naturally modelled as Boolean variables. In this paper we describe how to mimic a finite domain propagation engine, by mapping propagators into clauses in a SAT solver. This immediately results in strong nogoods for finite domain propagation. But a naive static translation is impractical except in limited cases. We show how to convert propagators to lazy clause generators for a SAT solver. The resulting system introduces flexibility in modelling since variables are modelled dually in the propagation engine and the SAT solver, and we explore various approaches to the dual modelling. We show that the resulting system solves many finite domain problems significantly faster than other techniques.
Data mining at NASA: from theory to applications
Authors: Ashok N. Srivastava
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

NASA has some of the largest and most complex data sources in the world, with data sources ranging from the earth sciences, space sciences, and massive distributed engineering data sets from commercial aircraft and spacecraft. This talk will discuss some of the issues and algorithms developed to analyze and discover patterns in these data sets. We will also provide an overview of a large research program in Integrated Vehicle Health Management. The goal of this program is to develop advanced technologies to automatically detect, diagnose, predict, and mitigate adverse events during the flight of an aircraft. A case study will be presented on a recent data mining analysis performed to support the Flight Readiness Review of the Space Shuttle Mission STS-119.
Problems of Data Quality in an Integrated Cadastral Information System
Authors: Dariusz Cieśla, Zbigniew Telec, Bogdan Trawiński, Robert Widz
Venue: Proceeding of the 2008 conference on New Trends in Multimedia and Network Information Systems (2008)

Cadastral systems belong to the most important public systems, since they provide necessary information for economic planning, spatial planning, and tax calculation, real estate denotation in perpetual books, public statistics, and real estate management as well as farm registration. They also provide source data to systems such as IACS and its main component LPIS. Quality of cadastral data has a major impact on the functioning many other systems. Legacy cadastral systems were developed using different data structures and various computer technologies. The quality of those legacy systems was sufficient for accomplishing everyday tasks but it was too low in the case of transferring data into other information systems. A practical approach to assure data quality in the process of transferring descriptive and geometric data from legacy systems into the Kataster OnLine-a modern integrated cadastral information system is presented in the paper.
Approximate linear-programming algorithms for graph-based Markov decision processes
Authors: Nicklas Forsell, Régis Sabbadin
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

In this article, we consider a form of compact representation of MDP based on graphs, and we propose an approximate solution algorithm derived from this representation. The approach we propose belongs to the family of Approximate Linear Programming methods, but the graph-structure we assume allows it to become particularly efficient. The proposed method complexity is linear in the number of variables in the graph and only exponential in the width of a dependency graph among variables.
The IMS-based control architecture of IPTV service
Authors: HyunSoon Shin
Venue: Proceedings of the 2nd conference on European computing conference (2008)

This paper designs for the IMS-based control architecture of the IPTV service on NGN, proposes the service control method. The proposed control architecture of the IPTV service adds the IPTV multicast session control function to the CSCF(Call Session Control Function) of IMS so that IMS can control not only the existing communication service but also the broadcasting service. And it adds the profile management functions of the HSS subscriber to management for the IPTV subscriber. Also by constructing the information management function of the multicast group and the information management function of service(contents) additionally, the IPTV service interworking with the functions of IMS is controlled.
Multiresolution Minimization of Renyi's Mutual Information for fetal-ECG Extraction
Authors: Fabio La Foresta, Nadia Mammone, Giuseppina Inuso, Francesco C. Morabito, Andrea Azzerboni
Venue: Proceeding of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008 (2009)

Fetal electrocardiogram (fECG) monitoring yields important information about the fetus condition during pregnancy and it consists in collecting electrical signals by some sensors on the body of the mother. In literature, Independent Component Analysis (ICA) has been exploited to extract fECG. Wavelet-ICA (WICA), a technique that merges Wavelet decomposition and INFOMAX algorithm for Independent Component Analysis, was recently proposed to enhance fetal ECG extraction. In this paper, we propose to enhance WICA introducing MERMAID as the algorithm to perform independent component analysis because it has shown to outperform INFOMAX and the other standard ICA algorithms.
Bilevel newsvendor models considering retailer with CVaR objective
Authors: Lu Cheng, Zhongping Wan, Guangmin Wang
Venue: Computers and Industrial Engineering (2009)

In this paper, the bilevel newsvendor model in two-echelon systems is presented. In this model, CVaR (conditional value-at-risk) measure is considered as the retailer's objective. We obtain an analytical solution when the product's demand is uniformly distribution. Several examples are given to illustrate our model and for comparable with the basic two-echelon newsvendor model. For the circumstance when the manufacturer knows the retailer's objective, we get a counter-intuitive result: the retailer's CVaR measure is larger when his objective is minimizing CVaR than that when his objective is maximizing the expected profit. The reason is that the manufacturer changes the wholesale price to maximize his own profit when he knows the retailer's objective is CVaR. Some effects of parameters (such as unit shortage penalty) on the optimal wholesale price and order quantity are also revealed in the paper.
Primary Research on Urban Mass Panic Based on Computational Methods for Experiments
Authors: Xi Chen, Qi Fei, Wei Li
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Base on the theory of computational methods of experiments and agent modeling technology, combining with sociology and psychology, the paper presents method of computational experiments for research of Urban Mass Panic (UMP). The method proposed a panic-information transmitting artificial system for computational experiments with agent modeling technology. The system planed two kinds of agents: social individual agents and panic alarming agents. Social individual agents are designed to simulate persons living common human society. These agents which contain the ability of panic information recognition, reflection and making different decision are simulated with some nonlinear methods, such as fuzzy neural network. Panic alarming agents are designed to simulate circumstance which engenders panic information or panic phenomenon. These agents collect information about panic and release information to social individual agents by different transmitting methods we can image. The paper also discusses how to carry through measurement to check the level of UMP by the information entropy theory dynamically.
Decentralized error-dependent transmission control for model-based estimation over a multi-access network
Authors: Ching-Ling Huang, Raja Sengupta
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

This paper is motivated by the estimation problem and active safety design for ITS. We investigate the performance of model-based estimation over a multi-access network and emphasizes on asymptotic time-averaged MSE while using error-dependent transmission control. The performance of this decentralized policy is analyzed and an improved policy is also proposed to achieve robustness in a shared channel. Our results suggest that, while designing communication logic for vehicular safety applications, dynamics of the system and channel congestion should be considered at the same time.
A Maximum Power Point Tracking Method Based on Extension Neural Network for PV Systems
Authors: Kuei-Hsiang Chao, Ching-Ju Li, Meng-Huei Wang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, a maximum power point tracking (MPPT) technique based on extension neural network (ENN) was proposed to make full utilization of photovoltaic (PV) array output power which depends on solar insolation and ambient temperature. The proposed ENN MPPT algorithm can automatically adjust the step size to track the PV array maximum power point (MPP). Compared with the conventional fixed step size perturbation and observation (P O) and incremental conductance (INC) methods, the presented method is able to effectively improve the dynamic response and steady state performance of the PV systems simultaneously. A theoretical analysis and the designed principle of the proposed method are described in detail. And some simulation results are made to demonstrate the effectiveness of the proposed MPPT method.
CCNA Virtual, Titanium Edition 2.0: Exam 640-802
Authors: William Tedder
Venue:  (2009)

This virtual network simulator is ideal for candidates studying for the new CCNA exam (640-802) who cannot afford thousands of dollars to set up their own Cisco home lab. Offering hands-on practice with routers and switches is critical for success on the CCNA exam, and this simulator uses drag-and-drop technology to create a simulated lab using an unlimited number of routers and switches. Also included are lab exercises and guidance to help students experiment with hundreds of configuration commands built into the simulator. Plus, 250 hands-on labs zero in on skills that are critical for exam success and an extensive Help menu is available to guide you through complex tasks.
Logic and Artificial Intelligence for Multi-Agent Systems
Authors: Marie Duží, Daniela Ďuráková, Pavel Děrgel, Petr Gajdoš, Jaroslav Müller
Venue: Proceeding of the 2007 conference on Information Modelling and Knowledge Bases XVIII (2007)

The project Logic and Artificial Intelligence for Multi-Agent Systems is briefly described and its structure is specified. First we introduce the underlying logical framework---the Transparent Intensional Logic (TIL). Then we provide a description of particular problem areas, viz. knowledge representation including geographical data, languages apt for agents communication, and process management. Finally, future research and trends are specified.
Relating research and teaching: learning from experiences and beliefs
Authors: Su White, Alastair Irons
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

The relationship between research and teaching has possible benefits and inherent tensions. Exploring the potentially beneficial relationship is of interest and possible value to faculty, students, and stakeholders. Much of the existing literature has described approaches using a vocabulary derived from the soft/applied social science fields of study, a view-point which may in some ways be problematic. This paper examines the relationship between research and teaching in the undergraduate curriculum from a perspective of the computing disciplines. It compares and contrasts evidence of the beliefs and experiences of faculty about the relationship between research and teaching. It presents and analyses the result of surveys which gathered data to explore their understandings inter-relationship of research and teaching; in the curriculum; and as it is delivered, and experienced in the lab, seminar room and lecture hall. This research builds on existing work developed in a preliminary study which examined ways in which synergies between research and teaching could be achieved, particularly in the 'hard/applied' areas of the curriculum. It analyses data from the 'research-intensive' and the 'teaching-intensive' institutions. Having identified typical activities in the computing disciplines, it places them in the context of existing theoretical models.
Detecting inconsistencies in the design of virtual environments over the web using domain specific rules
Authors: Haïthem Mansouri, Frederic Kleinermann, Olga De Troyer
Venue: Proceedings of the 14th International Conference on 3D Web Technology (2009)

Nowadays, 3D Virtual Environments (VEs) are being used over the web for various purposes such as education, collaborative working or social networking. Unfortunately, the development process of such environments remains a demanding task, often accessible only to VE experts despite the availability of a number of Virtual Reality (VR) authoring tools. On the other hand, VE experts are seldom domain experts. This implies that their knowledge on specific domains can most of the time be limited. This could lead to design errors or, as in most cases, longer development times and efforts as the development process become an iterative one involving many revisions. One way of accelerating this process is by making it possible to capture a specific knowledge of a domain and later use this knowledge to automatically check that the design of the VE meets the requirements of the domain. This way, we ensure the conformity of the VE to the requirements of the domain for which it is being developed and by extension also to the customer's requirements. As a result, development times and efforts can significantly be shortened, while reducing the likelihood of error making. This paper describes an extension to an existing approach called VR-WISE that focuses on reducing development times and efforts of VEs using domain oriented terminology and ontologies.
Evaluating Algorithms for Shared File Pointer Operations in MPI I/O
Authors: Ketan Kulkarni, Edgar Gabriel
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

MPI-I/O is a part of the MPI-2 specification defining file I/O operations for parallel MPI applications. Compared to regular POSIX style I/O functions, MPI I/O offers features like the distinction between individual file pointers on a per-process basis and a shared file pointer across a group of processes. The objective of this study is the evaluation of various algorithms of shared file pointer operations for MPI-I/O. We present three algorithms to provide shared file pointer operations on file systems that do not support file locking. The evaluation of the algorithms is carried out utilizing a parallel PVFS2 file system on an InfiniBand cluster and a local ext3 file system using a 8-core SMP. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Proto-predictive representation of states with simple recurrent temporal-difference networks
Authors: Takaki Makino
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable environments. SR-TDNs incorporate the structure of simple recurrent neural networks (SRNs) into temporal-difference (TD) networks to use proto-predictive representation of states. Although they deviate from the principle of predictive representations to ground state representations on observations, they follow the same learning strategy as TD networks, i.e., applying TD-learning to general predictions. Simulation experiments revealed that SR-TDNs can correctly represent states with an incomplete set of core tests (question networks), and consequently, SR-TDNs have better on-line learning capacity than TD networks in various environments.
Adaptive run-time prediction in heterogeneous environments
Authors: Christian Glasner, Jens Volkert
Venue: Proceedings of the 18th ACM international symposium on High performance distributed computing (2009)

In this article we describe an approach for the prediction of the run-time of jobs in heterogeneous environments that applies a meta-prediction algorithm working in multiple phases. For an efficient utilization of hardware resources, it is necessary to support schedulers with detailed information about the jobs that are going to be dispatched. One technique is to provide accurate forecasts of application run-times. A large number of current approaches focus on limited sets of prediction techniques (often linear ones) whereas most times only one is deployed on a dataset, ignoring the different characteristics that are "denoted" inherently by the data and therefore are not obvious. For that reason we are proposing an adaptive system for run-time prediction that offers a large set of different and differently parameterized predictors respectively, whereas only the appropriate prediction techniques for specifically filtered clusters of jobs are executed.
Photoshop Elements 6 For Dummies: For Dummies Computer/Tech
Authors: Barbara Obermeier, Ted Padova
Venue:  (2007)

Want to get more fun from your photos? To edit and enhance your pictures, fix flaws, and create greeting cards or cool photo projects to share? What about turning out some really professional prints with simply stunning color? Photoshop Elements can handle it, and Photoshop Elements 6 For Dummies gets you up and running on Elements in a hurry. Photoshop Elements 6 is a reasonably priced, full-featured, powerful image-editing program for Windows (Adobe stopped supporting Elements for Mac with version 4.) This colorful guide helps you make the most of all its coolest features. You'll quickly get familiar with the work area and all the tools; be able to find, organize, and manage your images; correct common mistakes; and explore fun ways to share your photos. Youll discover how to: Acquire images from your camera or scanner Organize your files and photos you so can quickly find what youre looking for Crop and straighten pictures, fix exposure, and clean up dust and scratches Create sharp and colorful images for printing Correct color, contrast, and clarity Combine multiple images into creative collages Use filters to create different effects Turn your photos into slide shows, movie files, or Web-hosted images Elements has something for everyone, from beginning dabblers to serious photo hobbyists to professionals. With plenty of full-color illustrations that show what you can achieve, this friendly guide will help you use Elements to make the most of your digital photos.