ppxscal/embedding_network huggingface dataset:
Neural Network-Based Load Prediction for Highly Dynamic Distributed Online Games
Authors: Vlad Nae, Radu Prodan, Thomas Fahringer
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

We propose a neural network-based prediction method for the future entity layout in massively multiplayer online games. Our service has the potential to timely foresee critical hot-spots in fast-paced First Person Shooter action games that saturate the game servers which no longer respond to user actions at the required rate. Using our service, proactive load balancing (and redistribution) actions can be triggered.We show results based on a realistic simulation environment that demonstrate the advantages of our method compared to other conventional ones, especially due to its ability to adapt to different load patterns.
On the Analysis of "Simple" 2D Stochastic Cellular Automata
Authors: Damien Regnault, Nicolas Schabanel, Éric Thierry
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

We analyze the dynamics of a two-dimensional cellular automaton, 2D Minority, for the Moore neighborhood (eight neighbors per cell) under fully asynchronous dynamics (where only one random cell updates at each time step). Even if 2D Minority seems a simple rule, from the experience of Ising models and Hopfield nets, it is known that models with negative feedback are hard to study. This automaton actually presents a rich variety of behaviors, even more complex than what was observed and analyzed in a previous work on 2D Minority for the von Neumann neighborhood (four neighbors per cell) [1], including particles and a wider range of stable configurations. Nevertheless our work suggests that predicting the behavior of this automaton although difficult is possible, opening the way to analyze the class of totalistic automata.
Ship Hulls, B-Spline Surfaces, and CAD/CAM
Authors: David Rogers, Steven Satterfield, Francisco Rodriguez
Venue: IEEE Computer Graphics and Applications (1983)

This integrated CAD/CAM system uses B-spline surfaces to model ship hulls and uses the resulting surface for the production of wooden towing tank models.
Does software reliability growth behavior follow a non-homogeneous Poisson process
Authors: Kai-Yuan Cai, De-Bin Hu, Cheng-Gang Bai, Hai Hu, Tao Jing
Venue: Information and Software Technology (2008)

It is widely believed in software reliability community that software reliability growth behavior follows a non-homogeneous Poisson process (NHPP) based on analyzing the behavior of the mean of the cumulative number of observed software failures. In this paper we present two controlled software experiments to examine this belief. The behavior of the mean of the cumulative number of observed software failures and that of the corresponding variance are examined simultaneously. Both empirical observations and statistical hypothesis testing suggest that software reliability behavior does not follow a non-homogeneous Poisson process in general, and does not fit the Goel-Okumoto NHPP model in particular. Although this new finding should be further tested on other software experiments, it is reasonable to cast doubt on the validity of the NHPP framework for software reliability modeling. The importance of the work presented in this paper is not only for the new finding which is distinctly different from existing popular belief of software reliability modeling, but also for the adopted research approach which is to examine the behavior of the mean and that of the corresponding variance simultaneously on basis of controlled software experiments.
ERP Systems Business Value: A Critical Review of Empirical Literature
Authors: Fotini Michailidou, Anthi-Maria Sergi, Euripidis Loukis
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

The business value generated by information and communication technologies (ICT) has been for long time a major research topic. Recently there is a growing research interest in the business value generated by particular types of information systems (IS). One of them is the Enterprise Resource Planning (ERP) systems, which are increasingly adopted by organizations for supporting and integrating keybusiness and management processes. The current paper initially presents a critical review of the existing empirical literature concerning the business value of the ERP systems, which investigates the impact of ERP systems adoption on various measures of organizational performance. Then is critically reviewed the literature concerning the related topic of critical success factors (CSFs) in ERP systems implementation, which aims at identifying and investigating factors that result in more successful ERP systems implementation that generate higher levels of value for organizations. Finally, future directions of research concerning ERP systems business value are proposed.
Ontology/data engineering based distributed simulation over service oriented architecture for network behavior analysis
Authors: Bernard P. Zeigler
Venue:  (2008)

As network uses increase rapidly and high quality-of-service (QoS) is required, efficient network managing methods become important. Many previous studies and commercial tools of network management systems such as tcpdump, Ethereal, and other applications have weaknesses: limited size of files, command line execution, and large memory and huge computational power requirement. Researchers struggle to find fast and effective analyzing methods to save maintenance budgets and recover from systematic problems caused by the rapid increment of network traffic or intrusions. The main objective of this study is to propose an approach to deal with a large amount of network behaviors being quickly and efficiently analyzed. We study an ontology/data engineering methodology based network analysis system. We design a behavior, which represents network traffic activity and network packet information such as IP addresses, protocols, and packet length, based on the System Entity Structure (SES) methodology. A significant characteristic of SES, a hierarchical tree structure, enables systems to access network packet information quickly and efficiently. Also, presenting an automated system design is the secondary purpose of this study. Our approach shows adaptive awareness of pragmatic frames (contexts) and makes a network traffic analysis system with high throughput and a fast response time that is ready to respond to user applications. We build models and run simulations to evaluate specific purposes, i.e., analyzing network protocols use, evaluating network throughput, and examining intrusion detection algorithms, based on Discrete Event System Specification (DEVS) formalism. To study speed up, we apply a web-based distributed simulation methodology. DEVS/Service Oriented Architecture (DEVS/SOA) facilitates deploying workloads into multi-servers and consequently increasing overall system performance. In addition to the scalability limitations, both tcpdump and Ethereal have a security issue. As well as basic network traffic information, captured files by these tools contain secure information: user identification numbers and passwords. Therefore, captured files should not allow to be leaked out. However, network analyses need to be performed outside target networks in some cases. The distributed simulation&mdash;allocating distributing models inside networks and assigning analyzing models outside networks&mdash;also allows analysis of network behaviors out of networks while keeping important information secured.
Extending drive-thru data access by vehicle-to-vehicle relay
Authors: Jing Zhao, Todd Arnold, Yang Zhang, Guohong Cao
Venue: Proceedings of the fifth ACM international workshop on VehiculAr Inter-NETworking (2008)

Recently, some researchers have performed extensive experiments to study the feasibility and performance of vehicle drive-thru access to roadside access points (APs). The experiments demonstrate that the duration of connectivity to the AP is limited. A drive-thru vehicle has an area of high signal strength near the AP, but experiences poor link quality when entering or exiting the AP coverage area. Since a vehicle spends a large portion of the connection time in this poor link quality area, the data throughput can be significantly reduced. This problem has been identified in several works, but a viable solution has yet to be identified. In this paper, we propose a vehicle-to-vehicle relay (V2VR) scheme which extends the service range of roadside APs and allows drive-thru vehicles to maintain high throughput within an extended range. Our solution is distributed and purely client-based, without any modification to the existing 802.11 APs. Through implementation and simulation, we demonstrate that the V2VR scheme can effectively extend the drive-thru access range and improve the network utilization for drive-thru vehicles.
Attribute Reduction Based on the Fuzzy Information Filter Operators
Authors: Fachao Li, Chao Gao, Chenxia Jin
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Fuzzy set theory and rough set theory are effective tools for dealing with incomplete and inaccurate knowledge of information systems. In this paper, for the difference of fuzzy equivalence relation matrix of the attributes in information system, by analyzing the shortcomings of the existing methods, we propose the axiomatic system of fuzzy information filter operators, and give several operational filter operators models, spell out an attribute reduction method based on fuzzy information filter operators (denoted by FIFO-RED for short); Finally, we analyze the characteristics and performance of FIFO-RED by a concrete example. And the results indicate that FIFO-RED can more effectively merge decision consciousness into information processing than FIE-RED, it has strong application value.
Decentralised coordination of low-power embedded devices using the max-sum algorithm
Authors: A. Farinelli, A. Rogers, A. Petcu, N. R. Jennings
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

This paper considers the problem of performing decentralised co-ordination of low-power embedded devices (as is required within many environmental sensing and surveillance applications). Specifically, we address the generic problem of maximising social welfare within a group of interacting agents. We propose a novel representation of the problem, as a cyclic bipartite factor graph, composed of variable and function nodes (representing the agents' states and utilities respectively). We show that such representation allows us to use an extension of the max-sum algorithm to generate approximate solutions to this global optimisation problem through local decentralised message passing. We empirically evaluate this approach on a canonical coordination problem (graph colouring), and benchmark it against state of the art approximate and complete algorithms (DSA and DPOP). We show that our approach is robust to lossy communication, that it generates solutions closer to those of DPOP than DSA is able to, and that it does so with a communication cost (in terms of total messages size) that scales very well with the number of agents in the system (compared to the exponential increase of DPOP). Finally, we describe a hardware implementation of our algorithm operating on low-power Chipcon CC2431 System-on-Chip sensor nodes.
An improved dynamic programming algorithm for coalition structure generation
Authors: Talal Rahwan, Nicholas R. Jennings
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of partitioning the set of agents into exhaustive and disjoint coalitions such that the social welfare is maximized. This coalition structure generation problem is extremely challenging due to the exponential number of partitions that need to be examined. Specifically, given n agents, there are O(nn) possible partitions. To date, the only algorithm that can find an optimal solution in O(3n) is the Dynamic Programming (DP) algorithm, due to Rothkopf et al. However, one of the main limitations of DP is that it requires a significant amount of memory. In this paper, we devise an Improved Dynamic Programming algorithm (IDP) that is proved to perform fewer operations than DP (e.g. 38.7% of the operations given 25 agents), and is shown to use only 33.3% of the memory in the best case, and 66.6% in the worst.
On image reconstruction algorithms for binary electromagnetic geotomography
Authors: Rafal Zdunek
Venue: Theoretical Computer Science (2008)

In this paper we discuss the selected image reconstruction methods of binary tomography in the context of their application to geophysical imaging. We restrict our considerations to a discrete version of high-frequency electromagnetic geotomography, which we label as Binary Electromagnetic Geotomography (BEG). Basically, such an imaging technique may be applied to detect subsurface anomalies (air-filled voids) whose attenuation coefficient is very low (nearly zero-value) and considerably different from that for the background. The assumption for a binary representation of the image to be reconstructed substantially relaxes image reconstruction problems related to ill-posedness that comes from an intrinsic limitation of an angular range of projections. We test two algorithms for binary tomography, where the penalty term is based on the Markov Random Field (MRF) model. The mean-field reference distribution and mean-field annealing are applied to estimate the global maximizer of the Gibbs-Boltzmann distribution associated with the objective function. We also apply the projected gradient algorithm that uses a binary steering. Very efficient implementations of the algorithms are also given. The numerical results are presented for noise-free, noisy, and real data.
Modelling, Simulation, and Performance Analysis of Business Processes Involving Ubiquitous Systems
Authors: Patrik Spieß, Dinh Khoa Nguyen, Ingo Weber, Ivan Markovic, Michael Beigl
Venue: Proceedings of the 20th international conference on Advanced Information Systems Engineering (2008)

A recent trend in Ubiquitous Computing is that embedded software (e.g. in production machines, wired or wireless networked sensors and actuators, or RFID readers) directly offers Web Services. This allows it to directly participate in IT business processes. Our work suggests an approach to assess and compare the performance of such hybrid process models. It critically evaluates BPEL, the standard instrument for creating executable process descriptions, for its support of the dynamic nature of ubiquitous services, e.g. due to device mobility and unreliable wireless communication.
HealthSense: classification of health-related sensor data through user-assisted machine learning
Authors: Erich P. Stuntebeck, John S. Davis,  II, Gregory D. Abowd, Marion Blount
Venue: Proceedings of the 9th workshop on Mobile computing systems and applications (2008)

Remote patient monitoring generates much more data than healthcare professionals are able to manually interpret. Automated detection of events of interest is therefore critical so that these points in the data can be marked for later review. However, for some important chronic health conditions, such as pain and depression, automated detection is only partially achievable. To assist with this problem we developed HealthSense, a framework for real-time tagging of health-related sensor data. HealthSense transmits sensor data from the patient to a server for analysis via machine learning techniques. The system uses patient input to assist with classification of interesting events (e.g., pain or itching). Due to variations between patients, sensors, and condition types, we presume that our initial classification is imperfect and accommodate this by incorporating user feedback into the machine learning process. This is done by occasionally asking the patient whether they are experiencing the condition being monitored. Their response is used to confirm or reject the classification made by the server and continually improve the accuracy of the classifier's decisions on what data is of interest to the health-care provider.
On Capacity of Memory in Chaotic Neural Networks with Incremental Learning
Authors: Toshinori Deguchi, Keisuke Matsuno, Naohiro Ishii
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

Neural networks are able to learn more patterns with the incremental learning than with the correlative learning. The incremental learning is a method to compose an associate memory using a chaotic neural network. In former work, it was found that the capacity of the network increases along with its size, which is the number of the neurons in the network, until some threshold size and that it decreases over that size. The threshold size and the capacity varied between 2 different learning parameters. In this paper, the capacity of the networks was investigated changing the learning parameter. Through the computer simulations, it turned out that the capacity also increases in proportion to the network size in larger sizes and that the capacity of the network with the incremental learning is above 11 times larger than the one with correlative learning.
All the Way to Living Independently: Reflections on a Design Case
Authors: Peter Brok, Ingrid Mulder, Jan Berg
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Even when assistive technologies do support people with special needs and enabling them to retain an independent lifestyle, unforeseen thresholds may pop up and hinder people to become fully independent. Aiming to contribute to best practices in the field of independent living, a co-design case of support for a specific person with serious speech and movement impairments is reported. We describe the human-centered design trajectory, the developed support, and reflect on our experiences striving to develop computer programs that really help people with special needs in order to maintain independent living.
Learning a Classifier with Very Few Examples: Analogy Based and Knowledge Based Generation of New Examples for Character Recognition
Authors: S. Bayoudh, H. Mouchère, L. Miclet, E. Anquetil
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

This paper is basically concerned with a practical problem: the on-the-fly quick learning of handwritten character recognition systems. More generally, it explores the problem of generating new learning examples, especially from very scarce (2 to 5 per class) original learning data. It presents two different methods. The first one is based on applying distortions on original characters using knowledge on handwriting properties like speed, curvature etc. The second one consists in generation based on the notion of analogical dissimilarity which quantifies the analogical relation "A is to B almost as C is to D". We give an algorithm to compute the k-least dissimilar objects D, hence generating k new objects from three examples A, B and C. Finally, we experimentally prove the efficiency of both methods, especially when used in conjunction.
'I Want My HDTV'? Underlying Factors of Perceived Usefulness for High Definition Television
Authors: Eva Baaren, Lidwien Wijngaert, Erik Huizer
Venue: Proceedings of the 6th European conference on Changing Television Environments (2008)

While traditional technology acceptance models concentrate on relationships between usefulness and acceptance, they leave unresolved the questions about why a certain technology is found useful, in which contexts, and by whom. This paper presents an empirical study of some of the factors behind perceived usefulness of HDTV in the Netherlands, where the adoption process has just begun. Results show that HDTV awareness, knowledge about HDTV, daily television viewing habits, household innovativeness and the presence of digital television contribute to perceived usefulness of HDTV characteristics. They also demonstrate that these characteristics accord with Dutch viewer demands for future television.
LS/ABPM - an agent-powered suite for goal-oriented autonomic BPM
Authors: Giovanni Rimassa, Martin E. Kernland, Roberto Ghizzioli
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: demo papers (2008)

In this paper we shortly describe the Living Systems&reg; Autonomic Business Process Management (LS/ABPM) software product. LS/ABPM is an integrated environment, based on J2EE, Eclipse and Agent Technology, to support agile Business Process Management through goal-oriented process modeling, autonomic business process navigation and a multi-layer extensible architecture. The product comprises a Process Development Suite, to model, execute and test business processes, and a Process Runtime Suite, to run, manage and control business process instances in a production environment. The innovation of LS/ABPM with respect to common BPM technologies lies both in the GO-BPMN modeling language, which enhances the standard BPMN with goal and plan structures and direct executability, and in the execution engine, which leverages the LS/TS multi-agent system platform to provide goal-oriented (BDI) process execution, runtime modifiability of process models for running instances and multi-instance cooperation and autonomic control.
Cognitive Dimensions of Notations: Understanding the Ergonomics of Diagram Use
Authors: Alan F. Blackwell
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

The Cognitive Dimensions of Notations framework provides an analytic approach to understanding the way that diagrams are used in real tasks. It is intended as a tool for people who need to invent new diagrams or notational conventions. It offers such practitioners a vocabulary with which to discuss the properties of the notation that will be cognitively relevant, and that are likely to have an impact on the usability of notational systems. This tutorial presents the original motivation for the framework, an illustrated overview of the vocabulary, and a survey of the tools that have been developed for applying the framework in practical design and research contexts.
A Fuzzy Timed Object-Oriented Petri Net for Multi-Agent Systems
Authors: Hua Xu, Peifa Jia
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

In this paper, a multi-agent system (MAS) modeling method called fuzzy timed object-oriented Petri nets (FTOPN) is proposed. FTO-PN has extended Petri nets (PN) supporting object-oriented modeling and temporal fuzzy learning based on timed hierarchical object-oriented Petri net (TOPN) and fuzzy timed Petri net (FTPN). Our focus is the adaptation according to TOPN concepts of cooperation objects for supporting synchronous and asynchronous communications and the temporal fuzzy learning proposed in FTPN. These two diagrams have been chosen because they are the most commonly used in modeling MAS and describing agent learning and reasoning ability. That is to say, they can be used to model and illustrate both the structural and dynamic aspects of MAS. Not only the proposed FTOPN can be used to model complex MAS, but also FTOPN model can be refined into the object-oriented implementation easily. It has bridged the gap between the formal modeling and the system refinement, which can overcome the development problems in agent-oriented software engineering. At the same time, it also can be regarded as a conceptual and practical artificial intelligence (AI) tool for the integration of MAS into the mainstream practice of software development.