ppxscal/embedding_network huggingface dataset:
Liemandt Foundation launches hidden agenda contest: university students vie for a $25,000 prize by building video games that secretly teach middle school subjects
Authors: Lauren Davis
Venue: Computers in Entertainment (CIE) (2003)

The Liemandt Foundation, a nonprofit family foundation focused on promoting technology-enabled education, launched on September 18, 2003 a college student video game development contest with a twist -- students are being challenged to build entertaining games that "secretly" teach middle school subjects.The contest, online at www.hiddenagenda.com, focuses on the notion of "stealth education" in gaming, pushing students to create primarily entertaining games that also teach science and math topics such as forces, statistics, or the solar system. Students have complete freedom in their game designs. They may work in teams of up to eight people, can build the games on and for any platform, and may use existing engines if they choose. Games will be judged in May 2004, with five finalist teams flying to Austin, Texas for their final shot at the $25,000 prize.Advising the contest are experts such as Ultima creator and gaming legend Richard Garriott and educational game visionary Marc Prensky, and the project is affiliated with the Digital Media Collaboratory at the University of Texas. "There is no doubt in my mind that college students can create the next breakthrough educational video game," says Garriott. Prensky agrees, "I look forward to watching these motivated and creative students break through the barriers of historically boring learning games." Among the many benefits of challenging college students to build the game is the notion that once these students enter the professional game development community, they will understand the importance and potential of stealth education.While all submitted games must fulfill teaching and technical requirements to be considered, final judging is based on 70% entertainment and 30% educational value. The uneven split in judging criteria is crucial. In the past, educational games have failed because no matter how well they taught, kids just weren't motivated to absorb information. Children will only learn from the games they want to play. 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
Application method for process frame-work
Authors: Kazutoshi Shimanaka, Junji Koga, Naoki Sugiwaka, Takeshi Sakamoto
Venue: Proceedings of the Tenth Asia-Pacific Software Engineering Conference Software Engineering Conference (2003)

Having analyzed the results of projects concludedsuccessfully in the last several years, we have shownproject management processes as quantitative data. Usingthose data, we have created a guideline for customizing theproject management processes. We have found outeffectiveness of the guideline by applying it to a couple ofpilot projects. The projects applied an iterative approach.Through the success of the pilot projects, we have alsodiscovered that the past data of a waterfall developmentstyle project can be used as analysis input for an iterativedevelopment project.
Evolutionary algorithms for statistics and finance
Authors: Vassilios N. Karavas
Venue:  (2003)

Several models in econometrics and finance have been proven to be computationally intractable due to their complexity. In this dissertation, we propose an evolutionary-genetic-algorithm for solving these types of problems. We extend the models so that less restrictive assumptions are required and we cope with the increased complexity by using a modified version of the evolutionary algorithm proposed for the simpler cases. More specifically, we study closer the estimation of switching regression models as introduced by Quandt (1958). The applicability of the proposed algorithms is examined through disequilibrium models; models that provide supply and demand functions for markets, when the price is not adjusted so that the quantity supplied equals the quantity demanded. We focus on the computational aspect of the deterministic switching regression models and we suggest a self-evolving genetic algorithm for solving these types of problems. As an illustration, we present results from Monte Carlo simulations and thereafter we apply the algorithm to the disequilibrium model proposed for the gasoline market during the &ldquo;energy crisis&rdquo;. We further extend the &ldquo;general model&rdquo; for markets in disequilibrium by incorporating dynamic relationships, and we examine the applicability of the proposed genetic algorithm in this more complex and realistic problem. Subsequently, the proposed genetic algorithm for the markets in disequilibrium is applied to financial models, where the structure and computational complexity are comparable with those of the switching regression models. As example, we apply the algorithm to minimizing portfolio tracking error with respect to a pre-specified index. The proposed genetic algorithm possesses unique characteristics that maximize the fitness of the algorithm itself for each individual problem. This is achieved through a Self-Evolving process that teaches the genetic algorithm what internal parameters improve the algorithm's fitness.
Evaluating Connectivity and Quality in Ad-Hoc Networks through Clustering and Trellis Algorithms
Authors: Martha Lucia Torres Lozano, César Vargas Rosales
Venue: Proceedings of the 14th International Conference on Electronics, Communications and Computers (2004)

Recently, wireless networks have become increasinglypopular in the computing industry. These networksprovide mobile users with ubiquitous computing capabilityand information access regardless of the location.There are currently two variations of mobile wirelessnetworks- infrastructured (e.g., cellular network) andinfrastructureless networks, called Mobile Ad-Hoc Networks,where the entire network is mobile, and the individualterminals are allowed to move at will, relative toeach other, then they are self-creating, self-organizing,and self-administering. In order to improve the usersservice, there exist some measures as connectivity,quality, throughput, and others, to permit evaluate theperformance in the network. In this work, we evaluateconnectivity and quality using clustering algorithms,DDCA (Distributed Dynamic Clustering Algorithm),and Trellis Method to find k-paths to the different users.
On the independence of equations in three variables
Authors: Tero Harju, Dirk Nowotka
Venue: Theoretical Computer Science (2003)

We prove that an independent system of equations in three variables with a nonperiodic solution and at least two equations consists of balanced equations only. For that, we show that the intersection of two different entire systems contains only balanced equations, where an entire system is the set of all equations solved by a given morphism. Furthermore, we establish that two equations which have a common nonperiodic solution have the same set of periodic solutions or are not independent.
Automatic graphs and D0L-sequences of finite graphs
Authors: Olivier Ly
Venue: Journal of Computer and System Sciences (2003)

The notion of end is a classical mean to understand the behavior of a graph at infinity. In this respect, we show that the problem of deciding whether an infinite automatic graph has more than one end is recursively undecidable. The proof involves the analysis of some global topological properties of the configuration graph of a self-stabilizing Turing machine. This result is applied to the graph transformation system theory: It allows us to set a picture of decidability issues concerning logic of D0L-languages of finite graphs. We first show that the first-order theory of a D0L-sequence of finite graphs is decidable. Secondly, we show that the first-order theory, when it is upgraded with a closure operator, becomes undecidable for D0L-sequences of finite graphs.
Reliable Real-Time Communication in CAN Networks
Authors: Luís Miguel Pinho, Francisco Vasques
Venue: IEEE Transactions on Computers (2003)

Abstract--Controller Area Network (CAN) is a fieldbus network suitable for small-scale Distributed Computer Controlled Systems (DCCS), being appropriate for sending and receiving short real-time messages at speeds up to 1 Mbit/sec. Several studies are available on how to guarantee the real-time requirements of CAN messages, providing preruntime schedulability conditions to guarantee the real-time communication requirements of DCCS traffic. Usually, it is considered that CAN guarantees atomic multicast properties by means of its extensive error detection/signaling mechanisms. However, there are some error situations where messages can be delivered in duplicate or delivered only by a subset of the receivers, leading to inconsistencies in the supported applications. In order to prevent such inconsistencies, a middleware for reliable communication in CAN is proposed, taking advantage of CAN synchronous properties to minimize the runtime overhead. Such middleware comprises a set of atomic multicast and consolidation protocols, upon which the reliable communication properties are guaranteed. The related timing analysis demonstrates that, in spite of the extra stack of protocols, the real-time properties of CAN are preserved since the predictability of message transfer is guaranteed.
A selective, multiple-criteria method for handling constraint violations in well-defined design problems
Authors: Argiris J. Dentsoras
Venue: Artificial Intelligence for Engineering Design, Analysis and Manufacturing (1999)

A selective, multiple-criteria method is proposed for handling constraint violations in well-defined design problems. First, the types of design problems upon which the method may apply are presented and a graph topology is adopted for representing the problem decomposition in the level of design parameter interrelations (design parameter graphs). Next, the problem of constraint violations for the design parameters is discussed. It is shown that these violations can be resolved by modifying the values of the primary design parameters and recalculating the values of the violated parameters. Any &ldquo;blind&rdquo; attempt of modifying the values of the primary design parameters for resolving occurring violations may, eventually, create additional violations. The proposed method guides the designer toward those primary design parameters that present the least possibility of creating more violations when their values are modified. This is achieved by applying multiple criteria and by producing a final, sorted list of primary design parameters. The designer may then choose the first element of this list to handle efficiently the violations of the design parameters. Two examples are given on a design space where constraint violations occur. Through these examples, the capability of the proposed method in helping the designer to handle constraint violation is shown. The concluding remarks, except for summarizing the potential of the method, determine its boundaries and include a reference on relative work currently under investigation.
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Authors: Eamonn Keogh, Jessica Lin, Wagner Truppel
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

Time series data is perhaps the most frequently encountered typeof data examined by the data mining community. Clustering isperhaps the most frequently used data mining algorithm, beinguseful in it's own right as an exploratory technique, and also as asubroutine in more complex data mining algorithms such as rulediscovery, indexing, summarization, anomaly detection, andclassification. Given these two facts, it is hardly surprising thattime series clustering has attracted much attention. The data to beclustered can be in one of two formats: many individual timeseries, or a single time series, from which individual time seriesare extracted with a sliding window. Given the recent explosion ofinterest in streaming data and online algorithms, the latter casehas received much attention.In this work we make an amazing claim. Clustering of streamingtime series is completely meaningless. More concretely, clustersextracted from streaming time series are forced to obey a certainconstraint that is pathologically unlikely to be satisfied by anydataset, and because of this, the clusters extracted by anyclustering algorithm are essentially random. While this constraintcan be intuitively demonstrated with a simple illustration and issimple to prove, it has never appeared in the literature.We can justify calling our claim surprising, since it invalidatesthe contribution of dozens of previously published papers. We willjustify our claim with a theorem, illustrative examples, and acomprehensive set of experiments on reimplementations ofprevious work.
A Semimartingale Backward Equation and the Variance-Optimal Martingale Measure under General Information Flow
Authors: Michael Mania, Revaz Tevzadze
Venue: SIAM Journal on Control and Optimization (2003)

We consider a financial market model, where the dynamics of asset prices are given by an Rd-valued continuous semimartingale and the information flow is right-continuous. Using the dynamic programming approach we express the variance-optimal martingale measure in terms of the value process of a suitable optimization problem and show that this value process uniquely solves the corresponding semimartingale backward equation. We consider two extreme cases when this equation admits an explicit solution. In particular, we give necessary and sufficient conditions in order that the variance-optimal martingale measure coincides with the minimal martingale measure as well as with the martingale measure appearing in the second extreme case.
Robust Solution to Fuzzy Identification Problem with Uncertain Data by Regularization
Authors: Mohit Kumar, Regina Stoll, Norbert Stoll
Venue: Fuzzy Optimization and Decision Making (2004)

This study considers the robust identification of the parameters describing a Sugeno type fuzzy inference system with uncertain data. The objective is to minimize the worst-case residual error using a numerically efficient algorithm. The Sugeno type fuzzy systems are linear in consequent parameters but nonlinear in antecedent parameters. The robust consequent parameters identification problem can be formulated as second-order cone programming problem. The optimal solution of this second-order cone problem can be interpreted as solution of a Tikhonov regularization problem with a special choice of regularization parameter which is optimal for robustness (Ghaoui and Lebret (1997). SAIM Journal of Matrix Analysis and Applications 18, 1035&ndash;1064). The final regularized nonlinear optimization problem allowing simultaneous identification of antecedent and consequent parameters is solved iteratively using a generalized Gauss&ndash;Newton like method. To illustrate the approach, several simulation studies on numerical examples including the modelling of a spectral data function (one-dimensional benchmark example) is provided. The proposed robust fuzzy identification scheme has been applied to approximate the physical fitness of patients with a fuzzy expert system. The identified fuzzy expert system is shown to be capable of capturing the decisions (experiences) of a medical expert.
Nano-scale compositional lamination of doped silica glass deposited in surface discharge plasma of SPCVD technology
Authors: A. V. Kholodkov, K. M. Golant, I. V. Nikolin
Venue: Microelectronic Engineering (2003)

The kinetics of metal halogenide mixture transformation into oxides was studied with the help of optical emission spectroscopy (OES) in the microwave-induced discharge of surface plasma chemical vapor deposition (SPCVD) process. The structure of germanium-doped silica layer deposited in plasmachemical synthesis of preforms for optical fiber drawing was also investigated. It was shown that deposited glass has a periodical structure of alternate layers with different glass composition. Observation experiments on the oxide formation kinetics in plasma column were performed for the interpretation of the lamination effect. It was demonstrated that the lamination effect is related to a non-uniform distribution of the corresponding monoxides along the plasma column. This lamination results from the competition of different chemical oxidation reactions for oxygen. On the basis of the results obtained, a set of chemical reactions responsible for the formation of multicomponent glasses in SPCVD-type processes is proposed.
The impact of load balancing to object-oriented query execution scheduling in parallel machine environment
Authors: David Taniar, Clement H. C. Leung
Venue: Information Sciences&mdash;Informatics and Computer Science: An International Journal (2003)

Skewness has been one of the major problems not only in parallel relational database systems, but also in parallel object-oriented database systems. To improve performance of object-oriented query processing, a careful and intelligent skew handling for load balancing must be established. Depending on the parallel machine environment, whether it is a shared-memory or a shared-nothing architecture, load balancing can be achieved through "physical" or "logical" data re-distribution. It is not the aim of this paper to propose or to investigate skew handling methods, but rather to analyze the impact of load balancing to query execution scheduling strategies. Our analysis shows that when load balancing is achieved, "serial" execution scheduling is preferable to "parallel" execution scheduling strategy. In other words, allocating full resources to a sub-query seems to be better than dividing resources to multiple sub-queries.
Using developmental theories to inform the design of technology for children
Authors: Peta Wyeth, Helen C. Purchase
Venue: Proceedings of the 2003 conference on Interaction design and children (2003)

Electronic Blocks are a new programming environment, designed specifically for children aged between three and eight years. As such, the design of the Electronic Block environment is firmly based on principles of developmentally appropriate practices in early childhood education. The Electronic Blocks are physical, stackable blocks that include sensor blocks, action blocks and logic blocks. Evaluation of the Electronic Blocks with both preschool and primary school children shows that the blocks' ease of use and power of engagement have created a compelling tool for the introduction of meaningful technology education in an early childhood setting. The key to the effectiveness of the Electronic Blocks lies in an adherence to theories of development and learning throughout the Electronic Blocks design process.
Expectations for a scientific collaboratory: a case study
Authors: Diane H. Sonnenwald
Venue: Proceedings of the 2003 international ACM SIGGROUP conference on Supporting group work (2003)

In the past decade, a number of scientific collaboratories have emerged, yet adoption of scientific collaboratories remains limited. Meeting expectations is one factor that influences adoption of innovations, including scientific collaboratories. This paper investigates expectations scientists have with respect to scientific collaboratories. Interviews were conducted with 17 scientists who work in a variety of settings and have a range of experience conducting and managing scientific research. Results indicate that scientists expect a collaboratory to: support their strategic plans; facilitate management of the scientific process; have a positive or neutral impact on scientific outcomes; provide advantages and disadvantages for scientific task execution; and provide personal conveniences when collaborating across distances. These results both confirm existing knowledge and raise new issues for the design and evaluation of collaboratories.
PEBL: Web Page Classification without Negative Examples
Authors: Hwanjo Yu, Jiawei Han, Kevin Chen-Chuan Chang
Venue: IEEE Transactions on Knowledge and Data Engineering (2004)

Abstract--Web page classification is one of the essential techniques for Web mining because classifying Web pages of an interesting class is often the first step of mining the Web. However, constructing a classifier for an interesting class requires laborious pre-processing such as collecting positive and negative training examples. For instance, in order to construct a ¿homepage¿ classifier, one needs to collect a sample of homepages (positive examples) and a sample of nonhomepages (negative examples). In particular, collecting negative training examples requires arduous work and caution to avoid bias. This paper presents a framework, called Positive Example Based Learning (PEBL), for Web page classification which eliminates the need for manually collecting negative training examples in preprocessing. The PEBL framework applies an algorithm, called Mapping-Convergence (M-C), to achieve high classification accuracy (with positive and unlabeled data) as high as that of a traditional SVM (with positive and negative data). M-C runs in two stages: the mapping stage and convergence stage. In the mapping stage, the algorithm uses a weak classifier that draws an initial approximation of ¿strong¿ negative data. Based on the initial approximation, the convergence stage iteratively runs an internal classifier (e.g., SVM) which maximizes margins to progressively improve the approximation of negative data. Thus, the class boundary eventually converges to the true boundary of the positive class in the feature space. We present the M-C algorithm with supporting theoretical and experimental justifications. Our experiments show that, given the same set of positive examples, the M-C algorithm outperforms one-class SVMs, and it is almost as accurate as the traditional SVMs.
A new approach to conceptual document indexing: building a hierarchical system of concepts based on document clusters
Authors: Martin Holub
Venue: Proceedings of the 1st international symposium on Information and communication technologies (2003)

We describe an original approach to conceptual document modeling. An abstract view of conceptual modeling is introduced and a method for building a hierarchical system of concepts based on analyzing large text collection and clustering documents is proposed. Then the concepts are employed in indexing documents in order to effectively examine and compare their contents and match them with queries.