ppxscal/embedding_network huggingface dataset:
The Tactics Generating of Intelligent Character Based on the Adaptive Rule Base of Dynamic Script
Authors: Zhaoyang Qu, Zhong Xin
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 03 (2009)

The intelligent character that possesses study ability, and can dynamically adapt to environmental changes has become one of the selling points featured by commercial games, since the traditional and artificially intelligent methods that have been adopted could not realize the act of complicated intelligent character. This passage puts forward the methods of how to generating tactics for intelligent character based on the adaptive rule base of dynamic script, and provides reasonable tactics for intelligent character through adaptive rule base of dynamic script in order that the intelligent character could adapt to the act of game players. In the simulation games related to practical power security rules, the test was carried out for the result executed by intelligent tactics, which has shown that the tactics provided by the adaptive rule base of dynamic script has greatly improved winning rate acted out by intelligent character.
A remote Chinese chess game using mobile phone augmented reality
Authors: Lieu-Hen Chen, Chi-Jr Yu, Shun-Chin Hsu
Venue: Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology (2008)

In this paper, we use Augmented Reality (AR) technology to implement a client-server Chinese chess game on mobile phones. Without a real chess board, users can play Chinese chess or learn "kifu" on the server. Kifu, recording every step in playing Chinese chess, is very helpful for players to learn and analyze the strategies for playing Chinese chess. Moreover, users can "directly" pick up a chess piece and move it through his mobile phone. This approach gives users the most natural human-computer interface. Because of the convenience of mobile phones, users do not need to sit in front of their computers or to buy an expensive device for AR technology (like HMD), and they can play board games ubiquitously and inexpensively with the system. With the wireless communication technology and client-server architecture, the system will not be restricted by storage memory and compute speed of any mobile phone. The system server can get AI of the advanced computer chess and numerous kifu resources from a "advanced Chinese chess knowledgebase system" developed by professor Shun-Chin Hsu.
Agent-based modeling of host-pathogen systems: The successes and challenges
Authors: Amy L. Bauer, Catherine A. A. Beauchemin, Alan S. Perelson
Venue: Information Sciences: an International Journal (2009)

Agent-based models have been employed to describe numerous processes in immunology. Simulations based on these types of models have been used to enhance our understanding of immunology and disease pathology. We review various agent-based models relevant to host-pathogen systems and discuss their contributions to our understanding of biological processes. We then point out some limitations and challenges of agent-based models and encourage efforts towards reproducibility and model validation.
Formal transformation of ontology axioms to application domain rules
Authors: Diana Kalibatiene, Olegas Vasilecas
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

Transformation rules can be defined in two ways -- theoretical and empirical. A theoretical-based definition of transformation is a formal way to prove and verify some theory. Therefore, it is precise, the likelihood of errors is reduced, it is easier to tell where it is wrong and correct it, and the quality of specification of the transformation can be improved. The disadvantage is the lack of knowledge about the theoretical-based approach. An empirical-based definition of transformation is informal and based on practice. Therefore, we can be sure that the transformation will work. However, sometimes it is impossible to verify some theory on practice or the cost of verification is too high. In this paper authors investigate the possibility of ontology axioms transformation to application domain rules using theoretical and empirical aspects.
Revenue Maximising Adaptive Auctioneer Agent
Authors: Janine Claire Pike, Elizabeth Marie Ehlers
Venue: Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems (2008)

Auction theory has proven that auction revenue is influenced by factors such as the auction format and the auction parameters. The Revenue Maximising Adaptive Auctioneer (RMAA) agent model has been developed with the aim of generating maximum auction revenue by adapting the auction format and parameters to suit the auction environment. The RMAA agent uses a learning classifier system to learn which rules are profitable in a particular bidding environment. The profitable rules are then exploited by the RMAA agent to generate maximum revenue. The RMAA agent model can effectively adapt to a real time dynamic auction environment.
INGRES: a relational data base system
Authors: G. D. Held, M. R. Stonebraker, E. Wong
Venue: Proceedings of the May 19-22, 1975, national computer conference and exposition (1975)

INGRES (Interactive Graphics and Retrieval System) is a relational data base and graphics system which is being implemented on a PDP-11/40 based hardware configuration at Berkeley. INGRES runs as a normal user job on top of the UNIX operating system developed at the Bell Telephone Laboratories. The only significant modification to UNIX that INGRES requires is a substantial increase in the maximum file size allowed. This change was implemented by the UNIX designers. The implementation of INGRES is primarily programmed in "C", a high level language in which UNIX itself is written. Parsing is done with the assistance of YACC, a compiler-compiler available on UNIX.
Sequence Mining Automata: A New Technique for Mining Frequent Sequences under Regular Expressions
Authors: Roberto Trasarti, Francesco Bonchi, Bart Goethals
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

In this paper we study the problem of mining frequent sequences satisfying a given regular expression. Previous approaches to solve this problem were focusing on its search space, pushing (in some way) the given regular expression to prune unpromising candidate patterns. On the contrary, we focus completely on the given input data and regular expression. We introduce Sequence Mining Automata ($SMA$), a specialized kind of Petri Net that while reading input sequences, it produces for each sequence all and only the patterns contained in the sequence and that satisfy the given regular expression. Based on this automaton, we develop a family of algorithms. Our thorough experimentation on different datasets and application domains confirms that in many cases our methods outperform the current state of the art of frequent sequence mining algorithms using regular expressions (in some cases of orders of magnitude).
Multilevel and multidimensional Hadamard matrices
Authors: Sarah Spence Adams, Matthew Crawford, Caitlin Greeley, Bryce Lee, Mathav Kishore Murugan
Venue: Designs, Codes and Cryptography (2009)

Multilevel Hadamard matrices (MHMs), whose entries are integers as opposed to the traditional restriction to {±1}, were introduced by Trinh, Fan, and Gabidulin in 2006 as a way to construct multilevel zero-correlation zone sequences, which have been studied for use in approximately synchronized code division multiple access systems. We answer the open question concerning the maximum number of distinct elements permissible in an order n MHM by proving the existence of an order n MHM with n elements of distinct absolute value for all n. We also define multidimensional MHMs and prove an analogous existence result.
A Chaotic Neural Network Combined Heuristic Strategy for Multidimensional Knapsack Problem
Authors: Ying Zhou, Zhanghui Kuang, Jiahai Wang
Venue: Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence (2008)

Multidimensional Knapsack Problem (MKP), as a classic combinatorial optimization problem, is used widely in various fields such as capital budgeting, allocating processors and databases in a distributed computer system. In this paper, a chaotic neural network combined heuristic strategy (TCNN-HS) is proposed for MKP. The proposed algorithm combines heuristic strategy which includes repair operator and improvement operator so that not only the infeasible solution can be overcome, but also the quality of the solutions can be improved. The TCNN-HS is tested on some benchmark problems, which is selected from OR library. Simulation results show that the proposed approach can find optimal solutions for some instances and outperforms TCNN.
Object Detection under Varying Illumination Based on Adaptive Background Modeling Considering Spatial Locality
Authors: Tatsuya Tanaka, Atsushi Shimada, Daisaku Arita, Rin-Ichiro Taniguchi
Venue: Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology (2009)

We propose a new method for background modeling. Our method is based on the two complementary approaches. One uses the probability density function(PDF) to approximate background model. The PDF is estimated non-parametrically by using Parzen density estimation. And foreground object is detected based on the estimated PDF. The other method is based on the evaluation of the local texture at pixel-level resolution while reducing the effects of variations in lighting. Fusing their approach realize robust object detection under varying illumination. Several experiments show the effectiveness of our approach.
Remote patient monitoring using GSM and GPS technologies
Authors: Mudasser F. Wyne, Vamsi K. Vitla, Praneethkar R. Raougari, Abdul G. Syed
Venue: Journal of Computing Sciences in Colleges (2009)

In this paper the authors describe the implementation and validation of a prototype of a Remote Patient Monitoring (RPM) system based on wireless technology using a pervasive device (such as a cellular phone), to send an SMS (Short Message Service) to the medical staff. The solution proposed by RPM system combines two commonly used technologies namely, Global System for Mobile (GSM) and Global Positioning System (GPS). The system provides an easy, viable, cheap and effective way for transmitting vital information to the healthcare providers. The system monitors patient's health status, such as spo2 (oxygen percentage in blood), heart rate, and temperature. Incase, the value for any of these parameters exceeds preset critical values, the position parameters, from the attached GPS module, are transmitted to pre-defined phone number in form of SMS using a GSM module. All the information obtained from the human body using a DSP (Digital Signal Processing) and an oximeter is then transmitted to the microcontroller system as digital values. The values obtained from DSP like SPO2, heart rate and temperature is also displayed on the LCD in alphanumerical form. The conclusion considers the implementation of future improvements to the health monitoring by introducing new sensors and by integrating alarm triggering algorithms and advanced security techniques.
Establishing relationships among patterns in stock market data
Authors: Dietmar H. Dorr, Anne M. Denton
Venue: Data Knowledge Engineering (2009)

Similarities among subsequences are typically regarded as categorical features of sequential data. We introduce an algorithm for capturing the relationships among similar, contiguous subsequences. Two time series are considered to be similar during a time interval if every contiguous subsequence of a predefined length satisfies the given similarity criterion. Our algorithm identifies patterns based on the similarity among sequences, captures the sequence-subsequence relationships among patterns in the form of a directed acyclic graph (DAG), and determines pattern conglomerates that allow the application of additional meta-analyses and mining algorithms. For example, our pattern conglomerates can be used to analyze time information that is lost in categorical representations. We apply our algorithm to stock market data as well as several other time series data sets and show the richness of our pattern conglomerates through qualitative and quantitative evaluations. An exemplary meta-analysis determines timing patterns representing relations between time series intervals and demonstrates the merit of pattern relationships as an extension of time series pattern mining.
ODMCA: An adaptive data mining control algorithm in multicarrier networks
Authors: Naixue Xiong, Laurence T. Yang, Yingshu Li
Venue: Computer Communications (2009)

Multicarrier communication is a promising technique to effectively deliver high data rate and combat delay spread over fading channel, and adaptability is an inherent advantage of multicarrier communication systems. It can be implemented in online data streams. This paper addresses a significant problem in multicarrier networks that arises in data streaming scenarios, namely, today's data mining is ill-equipped to handle data streams effectively, and pays little attention to the network stability and the fast response [http://www-db.standford.edu/stream]. Furthermore, in analysis of massive data streams, the ability to process the data in a single pass, while using little memory, is crucial. For often the data can be transmitted faster than it can be stored or accessed from disks. To address the question, we present an adaptive control-theoretic explicit rate (ER) online data mining control algorithm (ODMCA) to regulate the sending rate of mined data, which accounts for the main memory occupancies of terminal nodes. This single-pass scheme considers limited memory space to process dynamic data streams, and also explores the adaptive capability, which is employed in a general network computation model for dynamic data streams. The proposed method uses a distributed proportional integrative plus derivative (PID) controller combined with data mining, where the control parameters can be designed to ensure the stability of the control loop in terms of sending rate of mined data. The basic PID approach for the computation network transmission is presented and z-transformation and Schur-Cohn stability test are used to achieve the stability criterion, which ensures the bounded rate allocation without steady state oscillation. We further show how the ODMCA can be used to design a controller, analyze the theoretical aspects of the proposed algorithm and verify its agreement with the simulations in the LAN case and the WAN case. Simulation results show the efficiency of our scheme in terms of high main memory occupancy, fast response of the main memory occupancy and of the controlled sending rates.
Hierarchical Fuzzy Control for the Inverted Pendulum over the Set of Initial Conditions
Authors: Juliusz Zajaczkowski, Brijesh Verma
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

We examine hierarchical fuzzy control of the inverted pendulum over the set of initial conditions. A new compositional method for the inverted pendulum system is introduced. Three layered hierarchical fuzzy logic topology is used to create a fuzzy rule base for the control system. Fuzzy rules are learnt by evolutionary algorithm designed for the compositional method.
Fast searching for information on the Internet to use in a learning context: The impact of domain knowledge
Authors: Teena Willoughby, S. Alexandria Anderson, Eileen Wood, Julie Mueller, Craig Ross
Venue: Computers Education (2009)

The purpose of the study was to examine the role of domain knowledge when retrieving and using information from the Internet as a resource for essay tasks, as well as to investigate the quality of Internet searches and its relation to essay performance. In two experiments, 100 undergraduates searched the Internet for 30min and completed two essays; one in which they had high domain knowledge and one in which domain knowledge was low. Two control groups of 70 undergraduates just wrote the essays. Searching the Internet for information enhanced essay performance relative to the control groups only for the topic for which participants had high domain knowledge. In the second experiment, analyses of Internet searches revealed large individual differences in search behaviors and these behaviors did not relate to essay performance, although individuals highlighted the importance of domain knowledge in making their searches easier. Domain knowledge is one factor that educators should pay attention to when using the Internet for learning tasks, particularly when study time is limited, in order to maximize the ability of students to successfully retrieve and use information from the Internet.
An application layer multicast approach based on topology-aware clustering
Authors: Xinchang Zhang, Xiaodong Li, Wanming Luo, Baoping Yan
Venue: Computer Communications (2009)

Application layer multicast accelerates ubiquitous deployment of the multicast communication, as well as brings unavoidable performance penalties because the group members are dynamic and lack direct knowledge about the underlying topology. A promising approach to improve the multicasting performance is to cluster the nearby nodes in groups. However, it confronts some practical challenges. A challenge is that it is difficult to assign a proximity bound to determine whether some nodes should be clustered or not. Another practical problem is how to organize the corresponding multicast structure. In this paper, we propose a new topology-aware hierarchical clustering model, which implements clustering in different grain sizes. Based on the model, we propose an application layer multicast solution named HCcast, especially for large-scale group applications. HCcast employs a topology-aware approach to choose candidate parents at different levels, and uses distributed depth first searching (DFS) approach to position a host at the same level. The clusters of HCcast are topology-based, therefore cluster split and merge operations are unnecessary, which reduces the maintenance overhead. The results of our simulation experiments show that HCcast can build multicast trees with desirable delivery performance, and the performance keep stable in different join sequences.
DB2 Deployment Guide
Authors: IBM Redbooks
Venue:  (2008)

DB2 provides various installation methods as well as features and tools to deploy a large number of clients and servers. Database administrators, application developers, and application architects have a number of available options when deploying DB2 9.5 for Linux , UNIX , and Windows (DB2 for LUW). Focusing on the DB2 V9.5 deployment methodology, this IBM Redbooks publication provides general guidance and serves as a reference resource for DB2 based solution deployment. These techniques and considerations are also applicable to other recent versions of DB2 for LUW. Deployment begins at planning. We introduce various DB2 for LUW products to help you choose the right DB2 product for your enterprise. DB2 9.5 can be installed interactively using a graphical installer, or in a silent install where input is passed to the installer through a response file. We show details on how to deploy DB2 servers and clients to both single and multiple systems using the DB2 provided functions and features as well as a customized script. We also describe how to deploy DB2 through Microsoft System Management Server (SMS). In addition, we cover how to deploy DB2 with various applications, including JavaTM , C/C++, PHP, Python, Ruby, Perl, and .Net. Finally, we explain how to deploy a pre-configured database.
Finiteness of variance is irrelevant in the practice of quantitative finance
Authors: Nassim Nicholas Taleb
Venue: Complexity (2009)

Outside the Platonic world of financial models, assuming the underlying distribution is a scalable &ldquo;power law,&rdquo; we are unable to find a consequential difference between finite and infinite variance models&mdash;a central distinction emphasized in the econophysics literature and the financial economics tradition. Although distributions with power law tail exponents &alpha; > 2 are held to be amenable to Gaussian tools, owing to their &ldquo;finite variance,&rdquo; we fail to understand the difference in the application with other power laws (1 < &alpha; < 2) held to belong to the Pareto-L&eacute;vy-Mandelbrot stable regime. The problem invalidates derivatives theory (dynamic hedging arguments) and portfolio construction based on mean-variance. This article discusses methods to deal with the implications of the point in a real world setting. &copy; 2008 Wiley Periodicals, Inc. Complexity, 2009
Algebraic connectivity optimization via link addition
Authors: Huijuan Wang, Piet Van Mieghem
Venue: Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems (2008)

Significant research effort has been devoted to the topological features of complex networks to enhance the performance of dynamic processes implemented on these networks. In this work, we investigate how to optimize a network for a given dynamic process via a minor topological modification. The algebraic connectivity a(G) of a network G characterizes the performance of e.g. synchronization of dynamic processes at the nodes of the network G and random walks on networks which models e.g. the dispersion phenomena. We confine ourselves to the problem: "Where to add a link in a network G such that the algebraic connectivity is increased the most?" Exhaustive searching for the optimal link addition is computationally infeasible. Hence, we propose two strategies: 1. adding a link between the minimal degree node and a random other node; 2. adding a link between a node pair with the maximal |ui &minus; uj|, the absolute difference between the i &minus; th and j &minus; th elements of the Fiedler vector of G. Strategy 1 and 2 are compared with random link addition in three classes of networks: the Erd&ouml;s-R&eacute;nyi random graph, the BA model and the k-ary tree. The Fiedler vector based strategy 2 performs better than strategy 1. However, strategy 1 requires only local information, i.e. node degree.
Applying the Chilean Educational Experience in HCI to Peruvian Undergraduate and Graduate Programs
Authors: Jose Antonio Pow-Sang, Cristian Rusu, Claudia Zapata, Silvana Roncagliolo
Venue: Proceedings of the 2009 Second International Conferences on Advances in Computer-Human Interactions (2009)

The importance of Human-Computer Interaction (HCI) education for software professionals should be evident and well understood, when designing computing programs, at all levels. Unfortunately there is a lack of HCI courses in Peruvian computing programs. Changing curricula is often difficult and involves a long bureaucratic process. However, making small changes in courses' approach and emphasis only requires good will from the professors.The current paper presents a proposal to introduce HCI topics and/or courses in the Informatics Engineering curricula at Pontificia Universidad Católica del Perú, based on the Chilean educational experience at Pontificia Universidad Católica de Valparaíso.
How Hard Is It to Find Extreme Nash Equilibria in Network Congestion Games?
Authors: Elisabeth Gassner, Johannes Hatzl, Sven O. Krumke, Heike Sperber, Gerhard J. Woeginger
Venue: Proceedings of the 4th International Workshop on Internet and Network Economics (2008)

We study the complexity of finding extreme pure Nash equilibria in symmetric (unweighted) network congestion games. In our context best and worst equilibria are those with minimum respectively maximum makespan. On series-parallel graphs a worst Nash equilibrium can be found by a Greedy approach while finding a best equilibrium is NP-hard. For a fixed number of users we give a pseudo-polynomial algorithm to find the best equilibrium in series-parallel networks. For general network topologies also finding a worst equilibrium is NP-hard.