ppxscal/embedding_network huggingface dataset:
Transforming Raw-Email Data into Social-Network Information
Authors: Terrill L. Frantz, Kathleen M. Carley
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

We describe the technical background necessary for working with real-world email data as well as the process of how to transform it into a social-network representation for research purposes. We demonstrate how to use the CEMAP feature in ORA social-network analysis software, which operationalizes the entire process for researchers with, or without, in-depth computer expertise. A detailed example is provided to show the steps involved in the process and to highlight the various add-on features of CEMAP, such as anonymization and removing duplicate emails.
Advanced model reduction and simulation techniques for integrated electronic and thermal circuits
Authors: Sheldon X. Tan
Venue:  (2008)

As integrated circuit (IC) technologies step into nanometer regime, modeling and simulation of parasitic interconnects, which dominate the circuit performance, become a challenging problem. Model order reduction has been proved to be an efficient technique to reduce the complexity of interconnect circuits. However, existing model order reduction approaches loss their efficiency when the number of ports is large. One way to mitigate this long-standing problem is by means of combined terminal reduction and model order reduction. In this thesis, we first propose a new combined terminal and model reduction method, ESVDMOR, which utilizes higher order moment information during the terminal reduction and applies singular value decomposition low-rank approximation on input and output terminals separately. Second, a clustering based terminal reduction method, TermMerg, is proposed to find the dominant terminals of the circuit. TermMerg uses high order moments to build the input/output moment matrix, apply K-means clustering method to partition all terminals into different clusters, and select a representative terminal for each cluster. Finally, we propose a new decoupled terminal reduction strategy, MIRST, which considers the spatial correlation of the terminals and the temporal correlation of the input signals from design. Using this method, the original system can be partitioned into several subsystems, which only include fewer number of ports. Owning to increasing power consumption and the rapid heat generation on a die, efficient on-chip temperature regulation becomes imperative for today's high performance microprocessors. Temperature tracking based on software sensors is more flexible and comprehensive than on-chip physical thermal sensors, where temperature of any location is computed based on realtime power information. In this thesis, we propose three very efficient new thermal analysis methods, which are suitable for fast temperature tracking and runtime thermal regulation. The first method, TMMSpectrum, exploits the periodic patterns in power consumptions of the architecture modules in microprocessors and embedded high-performance systems. We propose to use spectrum analysis in frequency domain to compute the periodic responses of temperatures. The second method, TMMPWC, speeds up the thermal analysis by using piecewise constant average power inputs that determine the trend of temperature changes. The third algorithm, FEKIS, combines the Krylov sub-space reduction and the fixed large-step integration, to future speed up the simulation for the long power traces, which is specially suitable for runtime temperature tracking.
Network properties of a model for conscious and unconscious mental processes
Authors: Roseli S. Wedemann, Luís Alfredo Vidal de Carvalho, Raul Donangelo
Venue: Neurocomputing (2008)

We have previously described the mental pathology known as neurosis, in terms of its relation to memory function. We proposed neural network mechanisms, whereby neurotic behavior is described as a brain associative memory process, and the symbolic associativity involved in psychoanalytic working-through can be mapped onto a corresponding network reconfiguration process. Microscopic mechanisms that control synaptic properties self-organize the memory networks to a hierarchical, clustered structure. Modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. Here, we review these concepts and illustrate, with simulations, some of these complex networks' behaviors and properties.
MENN Method Applications for Stock Market Forecasting
Authors: Guangfeng Jia, Yuehui Chen, Peng Wu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

A new approach for forecasting stock index based on Multi Expression Neural Network (MENN) is proposed in this paper. The approach employs the multi expression programming (MEP) to evolve the architecture of the MENN and the particle swarm optimization (PSO) to optimize the parameters encoded in the MENN. This framework allows input variables selection, over-layer connections for the various nodes involved. The performance and effectiveness of the proposed method are evaluated using stock market forecasting problems and compared with the related methods.
Simulating Instructional Roles through Pedagogical Agents
Authors: Amy L. Baylor, Yanghee Kim
Venue: International Journal of Artificial Intelligence in Education (2005)

This paper describes the design and empirical validation of three distinct pedagogical agent roles (Expert, Motivator, and Mentor) for college students within the MIMIC (Multiple Intelligent Mentors Instructing Collaboratively) agent-based research environment. The pedagogical agent roles were operationalized by image, animation, affect, voice and script, and were developed in Poser 4 and implemented via Microsoft Agent. Two controlled experiments validated the instantiation of the three roles according to learner perception (N=78) and actual impact on motivation and learning (N=71). The results confirmed that the agent roles were not only perceived by the students to reflect their intended purposes but also led to significant changes in learning and motivation, as designed. Specifically, the Expert agent led to increased information acquisition, the Motivator led to increased self-efficacy, and the Mentor led to overall improved learning and motivation. The implications for intelligent tutoring and multi-agent system design and development is discussed.
Theoretical Foundations of Information Visualization
Authors: Helen C. Purchase, Natalia Andrienko, T. J. Jankun-Kelly, Matthew Ward
Venue: Information Visualization: Human-Centered Issues and Perspectives (2008)

The field of Information Visualization, being related to many other diverse disciplines (for example, engineering, graphics, statistical modeling) suffers from not being based on a clear underlying theory. The absence of a framework for Information Visualization makes the significance of achievements in this area difficult to describe, validate and defend. Drawing on theories within associated disciplines, three different approaches to theoretical foundations of Information Visualization are presented here: data-centric predictive theory, information theory, and scientific modeling. Definitions from linguistic theory are used to provide an over-arching framework for these three approaches.
A Privacy-Preserving Ticketing System
Authors: Kristof Verslype, Bart Decker, Vincent Naessens, Girma Nigusse, Jorn Lapon, Pieter Verhaeghe
Venue: Proceeedings of the 22nd annual IFIP WG 11.3 working conference on Data and Applications Security (2008)

Electronic identity (eID) cards are deployed in an increasing number of countries. These cards often provide digital authentication and digital signature capabilities, but have at the same time serious privacy shortcomings. We can expect that ordering and issuing tickets for events (e.g. soccer matches) will be increasingly done using eID cards, hence, severely threatening the user's privacy. This paper proposes two alternative ticketing systems that are using the eID card in a bootstrap procedure, but still are providing a high degree of privacy to the user.
Computer-Assisted Diagnosis of Primary Headaches
Authors: Svetlana Simić, Dragan Simić, Petar Slankamenac, Milana Simić-Ivkov
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Headache is not a disease which typically shortens one's life. However, it can be a serious social as well as a health problem. Approximately 27 billion euros per year are lost through reduced work productivity in the European Community. While the diagnostic criteria developed by the International Headache Society (IHS) have been extensively used in the epidemiological research, there is no such a tool which helps physicians make diagnoses. This research focussed on diagnosing certain primary headache types in working people employing the rule-based fuzzy logic system. The rules were facilitated by the application of the IHS criteria for headache types. Clinical experience was used to extend the established rules and improve the system. The proposed system is in the starting phase of the implementation at the Clinical Centre Vojvodina, Institute of Neurology in Novi Sad.
Coping with the dilemma of common pool information resourcing: Integrating information domains in the Dutch Police
Authors: Pieter Wagenaar, Stefan Soeparman
Venue: Information Polity (2004)

In a previous article in Information Polity [1] we looked into the question of whether integration of its information domains is leading to centralization in the Dutch police system. In this article we attempt to find out how such integration came about in the first place. Trying to establish an overall information management in or between organizations can be viewed as an attempt to create a common pool resource (CPR). Is hierarchy really the only way to establish such a CPR as, for instance, Davenport appears to assume? The experience of the Dutch police seems to point in a different direction. As it happens the 25 regional police forces, and the national police services have formed a 'Board of Direction' (Regieraad) in which the Ministry of Justice and the Home Office also partake. These parties are to decide on the shaping and operating of the police's information systems on the basis of equality. All evidence seems to point to the fact that this has been accomplished without making use of hierarchy. If we want to account for the Dutch police's success in establishing an overall information management without making use of hierarchy, there are three explanations that stand out in the available literature. These are Kollock's application of Ostrom's design principles of communities successful in creating CPRs to electronic environments, Monge, Fulk and Flanagin's stress on the advantages that fall to those who found a CPR, and Scharpf's concept of `negotiation in the shadow of hierarchy'. In this article we try to establish which one of the three holds good in the case of the Dutch police.
Create a mobile video story
Authors: Jari Multisilta, Marjo Mäenpää
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

The aim of this Artwork & Demo is to present a new mobile social video service and demo platform MoViE that enables users to create mobile narrations and stories using narrative structures. Visitors of the conference will be able to contribute to this service during the conference using their mobile phones or phones available at the booth. Automatically generated video stories or montages are created and presented based on the video clips visitors produce.
Mechanism and Localization of Wall Failure During Abdominal Aortic Aneurysm Formation
Authors: Dominik Szczerba, Robert Mcgregor, Krishnamurthy Muralidhar, Gábor Székely
Venue: Proceedings of the 4th international symposium on Biomedical Simulation (2008)

Our previously presented model of abdominal aneurysm formation allowed to simulate aneurysm dynamics relying on a postulated initial wall failure without being able to predict the actual location of such weakening. In this study we investigate what factors can trigger pathology progression at positions eventually observed in reality. We consider mechanical effects inside the arterial wall and their possible contributions to the formation of an aneurysm. Using a computer model we demonstrate the existence of wall regions susceptible to failure due to increased oscillatory mechanical loading. We find these regions to be uniquely correlated with actually observed aneurysm locations. We demonstrate that wall fatigue and failure are probable factors influencing the formation of an abdominal aortic aneurysm.
Critical and Steady State for Epidemic Dynamics on the Stationary Growth Networks
Authors: Shujuan Peng, Yuanxiang Li, Ying Peng
Venue: Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 02 (2008)

This paper discusses the dynamics of the epidemic spreading susceptible-infected-recovery (SIR) model on the stationary growth networks, relating them to the node-connectivity distribution that characterizes the network. We introduce the interaction Markov chains mean-field equations and the stochastic numerical approach to examine the threshold (steady state) and time-independent behaviour for the epidemic model on such network. Analytical methods and simulated experiments show there exhibits a critical threshold for the infinite size networks with the exponent less than or equal to 3 below which it cannot diffuse in such type of the system. For the BA networks, we present analytical and Monte Carlo calculations and compare the results with those obtained by the numerical method, which indicates stochastic numerical approach (SNA) can save memory and get the fast exploration.
Fully Adaptive Power Saving Protocols for Ad Hoc Networks Using the Hyper Quorum System
Authors: Shan-Hung Wu, Ming-Syan Chen, Chung-Min Chen
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Quorum-based Power Saving (QPS) protocols have been proposed for ad hoc networks (e.g., IEEE 802.11 ad hoc mode) to increase energy efficiency and prolong the operational time of mobile stations. These protocols assign to each station a cycle pattern that specifies when the station should wake up (to transmit/receive data) and sleep (to save battery power). In all existing QPS protocols, the cycle length is either identical for all stations or is restricted to certain numbers (e.g. squares or primes). These restrictions on cycle length severely limit the practical use of QPS protocols as each individual station may want to select a cycle length that is best suited for its own need (in terms of remaining battery power, tolerable packet delay, and drop ratio). In this paper we propose the notion of Hyper Quorum System (HQS)---a generalization of QPS that allows for arbitrary cycle lengths. We describe algorithms to generate two different classes of HQS given any set of arbitrary cycle lengths as input. We then present analytical and simulation results that show the benefits of HQS-based power saving protocols over the existing QPS protocols.
Search techniques for multi-objective optimization of mixed-variable systems having stochastic responses
Authors: Jennifer G. Walston
Venue:  (2007)

A research approach is presented that extends the separate solution methods of stochastic and multi-objective optimization problems to one that would solve problems having both characteristics. Such problems are typically encountered when one desires to optimize systems with multiple, often competing, objectives that do not have a closed form representation and must be estimated, e.g., via simulation. First, the class of mesh adaptive direct search (MADS) algorithms for nonlinearly constrained optimization is extended to mixed variable problems, and convergence to appropriately defined stationary points is proved. The resulting algorithm, MV-MADS, is then extended to stochastic problems (MVMADS-RS), via a ranking and selection procedure. Finally, a two-stage method is developed that combines the generalized pattern search/ranking and selection (MGPS-RS) algorithms for single-objective, mixed variable, stochastic problems with a multi-objective approach that makes use of interactive techniques for the specification of aspiration and reservation levels, scalarization functions, and multi-objective ranking and selection. This combination is devised specifically so as to keep the desirable convergence properties of MGPS-RS and MVMADS-RS, while extending to the multi-objective case. A convergence analysis for the general class of algorithms establishes almost sure convergence of an iteration subsequence to stationary points appropriately defined in the mixed-variable domain. Seven specific instances of the new algorithm are implemented and tested on 11 multi-objective test problems from the literature and an engineering design problem. 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
Comparing libraries for generic programming in haskell
Authors: Alexey Rodriguez, Johan Jeuring, Patrik Jansson, Alex Gerdes, Oleg Kiselyov, Bruno C. d. S. Oliveira
Venue: Proceedings of the first ACM SIGPLAN symposium on Haskell (2008)

Datatype-generic programming is defining functions that depend on the structure, or "shape", of datatypes. It has been around for more than 10 years, and a lot of progress has been made, in particular in the lazy functional programming language Haskell. There are morethan 10 proposals for generic programming libraries orlanguage extensions for Haskell. To compare and characterise the many generic programming libraries in atyped functional language, we introduce a set of criteria and develop a generic programming benchmark: a set of characteristic examples testing various facets of datatype-generic programming. We have implemented the benchmark for nine existing Haskell generic programming libraries and present the evaluation of the libraries. The comparison is useful for reaching a common standard for generic programming, but also for a programmer who has to choose a particular approach for datatype-generic programming.
About artificial intelligence methods: fuzzy logic engines and Bayesian filters
Authors: Claudiu Pozna, Catalin Alexandru
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

In this paper we analyze two methods of artificial intelligence: the Bayesian filter and the fuzzy logic engine. In order to do this we analyze each method and compare them. The paper ends with an case study of a fuzzy logic engine which is integrated into a Bayesian filter.
Adaptive Modeling and High Quality Spectral Estimation for Speech Enhancement
Authors: Luís Coelho, Daniela Braga
Venue: Proceedings of the 8th international conference on Computational Processing of the Portuguese Language (2008)

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.
Case based reasoning for predicting multi-period financial performances of technology-based SMEs
Authors: Tae Hee Moon, So Young Sohn
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Recently, various types of technology funds became available to support the programs for technology development and commercialization of SMEs (Small and Medium Enterprise) in Korea. However, the potential financial performances have not been sufficiently considered at the selection stage of fund recipient SMEs whereas the default risk has been a major concern. This paper proposes a CBR (Case Based Reasoning) system with GA (Genetic Algorithm) for predicting the EWMA (Exponentially Weighted Moving Average) of multi period financial performances of technology-oriented SMEs. It is expected that the proposed model can be applied to a wide range of technology investment related decision-making procedures.
A Segmentation Method for Digital Images Based on Cluster Analysis
Authors: Héctor Allende, Carlos Becerra, Jorge Galbiati
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

We present a method for image segmentation, that is, to identify image points with an indication of the region or class they belong to. The proposed algorithm basically consists of two stages. First it starts by restoring the image from possible contamination. In the second stage it analyzes each pixel using a 3x3 sliding window. For the first pixel, it creates an objets consisting of that same pixel, and registers this object in an array. In the subsequent steps, a cluster analysis is applied to the surrounding eight pixels, an determines whether the central pixel belongs to one of the existing objects, or a new object has to be created, and registered in the array of objects.
The full story of the Si$_{6}$ magic cluster
Authors: Aristides D. Zdetsis
Venue: Journal of Computational Methods in Sciences and Engineering (2007)

The structural, electronic, dynamical and spectral properties of Si$_{6}$ and its ions (Si$_{6}^{1-}$, Si$_{6}^{2-}$, and Si$_{6}^{1+})$ have been examined using a variety of high level ab initio techniques, including quadratic configuration interaction, coupled cluster, and density functional theory (DFT) with the hybrid B3LYP functional. Various high quality correlation-consistent basis sets, ranging from 2Z up to 5Z quality, were employed for the DFT calculations. It is shown that not only the ground state structure, but also the structure of the excited states, as well as the structure of the anions and cations of Si$_{6}$ are controversial. Each one of the three competing structures for the ground state, with C$_{s}$/C$_{2v}$, D$_{4h}$, and C$_{2v}$ symmetry, has been considered by different investigators as the lowest energy structure either of the neutral cluster, or of its anion or cation (or both). In a spirit of "structural democracy" it is demonstrated that the C$_{s}$/C$_{2v}$, D$_{4h}$, and $_{2v}$ structures can be safely assigned as the ground states of the neutral, anion, and cation clusters respectively. The present results, which support the structural plasticity (fluxionality) of Si$_{6}$, are in excellent agreement with experiment, including Raman and IR spectra, ionization energies, electron affinities as well as vibrationally resolved photoelectron spectra. The paradigm of Si$_{6}$ could be very helpful for other silicon clusters as well.