ppxscal/embedding_network huggingface dataset:
Technology Lessons For The Classroom: Office Applications Volume 2
Authors: Charlotte Haley, Rene Fuller, David Hoerger
Venue:  (2007)

Time-saving, Lifesaver lessons that are ready to use in the classroom! Project lessons are learner-centered and great for students as they take responsibility for their own learning and are engaged in the activity. Each lesson plan includes teacher and student instructions, With a strong emphasis on graphic manipulation. These lesson plans emphasize using office applications for real-world scenarios and reinforce critical thinking skills. Additional teaching resources are included such as examples, solution files, presentations to introduce specific topics, and three WebQuests. Grades 8-12 Lessons Include: * Bloom's Taxonomy * Rubrics that are easy for students to understand * A wrap-up reflection for students * Beginner, Intermediate, and Advanced lessons * Support of PDAS (Professional Development and Appraisal System - Domains I, II, and IV) goals as they incorporate active, successful student participation in learning Features: * Modifications for resource students as well as talented and gifted students * Suggested grade level for each lesson (8-9 or 10-12) * Timeframe estimates allow teachers to plan ahead Lesson plans that cover essential knowledge and skills for Business Education and Technology Applications classes. The effort that has gone into creating lessons that teach what needs to be taught and yet can be enjoyed by students is amazing. Topics Include: * Business Card * Photo Collage * Create an Animated Story in PowerPoint * A Lesson in Scanning * T-Shirt Design * Web Page Design * School Newspaper * Sign Language * Top 10 Cities * Travel Brochure * Like a Rock * Literary Characters * Music Database * National Parks * News Production * Keyboarding Games * News Reporter * Payroll * Polling and Sampling * Thank You Letter * This Day in History * Create a Personal Yearbook * Placing Images Inside ClipArt using Adobe Photoshop * Letterhead * Me and My Buddy * Oil and Gas * Remember to be Thankful! * Alliteration * Student Stats * Budget Conscious
Optimal Combination of SOM Search in Best-Matching Units and Map Neighborhood
Authors: Mats Sjöberg, Jorma Laaksonen
Venue: Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps (2009)

The distribution of a class of objects, such as images depicting a specific topic, can be studied by observing the best-matching units (BMUs) of the objects' feature vectors on a Self-Organizing Map (SOM). When the BMU "hits" on the map are summed up, the class distribution may be seen as a two-dimensional histogram or discrete probability density. Due to the SOM's topology preserving property, one is motivated to smooth the value field and spread out the values spatially to neighboring units, from where one may expect to find further similar objects. In this paper we study the impact of using more map units than just the single BMU of each feature vector in modeling the class distribution. We demonstrate that by varying the number of units selected in this way and varying the width of the spatial convolution one can find an optimal combination which maximizes the class detection performance.
Possibilistic evidential clustering
Authors: Anas Dahabiah, John Puentes, Basel Solaiman
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

An approach for clustering objects containing imperfect and heterogeneously-assigned data is proposed. This approach depends mainly on possibility theory to estimate the similarity between objects, and on belief theory and multidimensional scaling methods to assign relevant classes to them. This unsupervised clustering method has been applied to a medical database and robust results have been obtained with the absence of any a priori medical knowledge, and without knowing the key attributes of the concerned pathologies.
Teach Yourself VISUALLY Laptops: Teach Yourself VISUALLY Tech
Authors: Nancy C. Muir
Venue:  (2007)

Visual learners will find clear, step-by-step screen shots that show how to tackle more than 150 tasks related to using a laptop. Each task-based spread includes easy, visual directions for such operations as comparing different laptop models, using the keyboard and touchpad, connecting to a wireless network, adding PC cards and input devices, securing an Internet connection, setting up a low-battery alarm , and more. Helpful sidebars offer practical tips and tricks, while full-color screen shots demonstrate each task.
Robust extraction of named entity including unfamiliar word
Authors: Masatoshi Tsuchiya, Shinya Hida, Seiichi Nakagawa
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper proposes a novel method to extract named entities including unfamiliar words which do not occur or occur few times in a training corpus using a large unannotated corpus. The proposed method consists of two steps. The first step is to assign the most similar and familiar word to each unfamiliar word based on their context vectors calculated from a large unannotated corpus. After that, traditional machine learning approaches are employed as the second step. The experiments of extracting Japanese named entities from IREX corpus and NHK corpus show the effectiveness of the proposed method.
On the Connection between Interval Size Functions and Path Counting
Authors: Evangelos Bampas, Andreas-Nikolas Göbel, Aris Pagourtzis, Aris Tentes
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

We investigate the complexity of hard counting problems that belong to the class #P but have easy decision version; several well-known problems such as #Perfect Matchings, #DNFSat share this property. We focus on classes of such problems which emerged through two disparate approaches: one taken by Hemaspaandra et al. [1] who defined classes of functions that count the size of intervals of ordered strings, and one followed by Kiayias et al. [2] who defined the class TotP, consisting of functions that count the total number of paths of NP computations. We provide inclusion and separation relations between TotP and interval size counting classes, by means of new classes that we define in this work. Our results imply that many known #P-complete problems with easy decision are contained in the classes defined in [1]--but are unlikely to be complete for these classes under certain types of reductions. We also define a new class of interval size functions which strictly contains FP and is strictly contained in TotP under reasonable complexity-theoretic assumptions. We show that this new class contains some hard counting problems.
Ontology Integration Using Mappings: Towards Getting the Right Logical Consequences
Authors: Ernesto Jiménez-Ruiz, Bernardo Cuenca Grau, Ian Horrocks, Rafael Berlanga
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

We propose a general method and novel algorithmic techniques to facilitate the integration of independently developed ontologies using mappings. Our method and techniques aim at helping users understand and evaluate the semantic consequences of the integration, as well as to detect and fix potential errors. We also present ContentMap, a system that implements our approach, and a preliminary evaluation which suggests that our approach is both useful and feasible in practice.
Decision Rules and Arguments in Defeasible Decision Making
Authors: Edgardo Ferretti, Marcelo L. Errecalde, Alejandro J. García, Guillermo R. Simari
Venue: Proceeding of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008 (2008)

In this paper we present a model for defeasible decision making that combines decision rules and arguments. In this decision framework we can change the agent's decision policy in a flexible way, with minor changes in the criteria that influence the agent's preferences and the comparison of arguments. Our approach includes a simple methodology for developing the decision components of the agent. A decision framework designed with this methodology exhibits some interesting properties. If the agent (decision maker) has available all the relevant knowledge about its preferences among the different alternatives that could be conceivably posed to it, then our proposal implements a rational preference relation. In opposition, if the agent has partial knowledge about its preferences, the decisions made by the agent still exhibits a behavior consistent with the weak axiom of revealed preference of the choice-based approach, a more flexible approach to Individual Decision Making than the preference-based approach. The principles stated in this work are exemplified in a robotic domain, where a robot should make decisions about which box must be transported next.
The effects of phenology on indirect measures of aboveground biomass in annual grasses
Authors: H. S. Butterfield, C. M. Malmstrom
Venue: International Journal of Remote Sensing (2009)

Remote sensing is increasingly being used to quantify vegetation biomass across large areas, often with algorithms based on calibrated relationships between biomass and indices such as the normalized difference vegetation index (NDVI). To improve capacity to evaluate grassland dynamics over time, we examined the influence of phenological changes on NDVI-biomass relationships in annual grasses. Our findings support the use of NDVI throughout early growth and the beginning stages of canopy maturation, but suggest caution for later stages. In contrast, measurements of fractional photosynthetically active radiation (fAPAR) absorbed by the canopy and leaf area index (LAI) served as good season-long surrogates for canopy biomass. Canopies reached maximum biomass approximately 40 days after maximum greenness, with biomass increasing by approximately 20% during senescence. For multi-year studies of management impact (i) avoid using seasonal comparisons from dates much after the point of maximum greenness or (ii) consider non-NDVI-based approaches.
UICO: an ontology-based user interaction context model for automatic task detection on the computer desktop
Authors: Andreas S. Rath, Didier Devaurs, Stefanie N. Lindstaedt
Venue: Proceedings of the 1st Workshop on Context, Information and Ontologies (2009)

'Understanding context is vital' [1] and 'context is key' [2] signal the key interest in the context detection field. One important challenge in this area is automatically detecting the user's task because once it is known it is possible to support her better. In this paper we propose an ontology-based user interaction context model (UICO) that enhances the performance of task detection on the user's computer desktop. Starting from low-level contextual attention meta-data captured from the user's desktop, we utilize rule-based, information extraction and machine learning approaches to automatically populate this user interaction context model. Furthermore we automatically derive relations between the model's entities and automatically detect the user's task. We present evaluation results of a large-scale user study we carried out in a knowledge-intensive business environment, which support our approach.
An input panel and recognition engine for on-line handwritten text recognition
Authors: Rafael Ramos-Garijo, Sergio Martín, Andrés Marzal, Federico Prat, Juan Miguel Vilar, David Llorens
Venue: Proceeding of the 2007 conference on Artificial Intelligence Research and Development (2007)

A portable input panel and a real-time recognition engine for isolated, handwritten characters are presented. The input panel mimics the one found in standard pen-centered interfaces and the recognition engine is based on approximate Dynamic Time Warping comparisons with prototypes selected by two different fast classification procedures. The error rate obtained on the standard Pendigits task, 0.83%, is significantly lower than the error rate of other recently published techniques.
The Effects of Timing Dependence and Recursion on Parallel Program Schemata
Authors: Yasuo Matsubara, Takahiro Shakushi
Venue: Proceedings of the 4th International Symposium on High Performance Computing (2009)

We are interested in the effects of timing dependence and recursion in the class of parallel program schemata. We compare the expression power of some classes of dataflow schemata: UDF, DF ¿, RDF etc. DF ¿ includes a ¿-gate which introduces timing dependence, and RDF has a facility for recursion and UDF has both devices. In conclusion, we show some inclusion relations between classes, including the existence of a class standing between EF and EF d . These relations reveal the role of timing dependence and recursion.
An innovative perspective on mapping in grids
Authors: Ivanoe De Falco, Domenico Maisto, Umberto Scafuri, Ernesto Tarantino, Antonio Della Cioppa
Venue: Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems (2009)

To execute large scale applications exploiting the unemployed aggregated power available on grid nodes, effective and efficient mapping algorithms must be designed. Since the problem of optimally mapping is NP--complete, heuristic techniques can be profitably adopted to find near--optimal solutions. Here a multiobjective Differential Evolution algorithm is implemented and tested on different mapping scenarios with the aim to fulfill several optimization criteria. The results attained show the robustness of the evolutionary approach proposed in dealing with multisite grid mapping.
Plenary lecture 7: measures, rates of change for solutions to elliptic and parabolic equations and square functions
Authors: Caroline Sweezy
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

The rate of change of a temperature function in a confined region in Euclidean space, when there are heat sources within the domain, is of interest in physical applications. Starting with results concerning how the gradient of a temperature function with no internal sources can be controlled by the temperature on the boundary of a domain, we examine how the methods that have been successful in this situation can be changed to obtain similar information when heat sources are present. Certain techniques were used by Wheeden and Wilson, and later by the speaker and Wilson, to establish sufficient conditions on two measures, one, µ, on the interior of a bounded domain, Ω, and the other measure vdw on the boundary of Ω, so there is a constant C > 0, such that (∫Ω|∇u(x)|qdµ)1/q ≤ C (∫∂Ω|f(x′)|pv(x′)dw(x′))1/p for any solution u(x) to the Dirichlet problem, Δu = 0 in Ω, u|∂Ω = f. These methods can be adapted for solutions to the inhomogeneous equation, Lu = g in Ω, u|∂Ω = 0, to show that the rate of change of u is bounded by the heat source function, g. The history of work on both problems will be discussed, and results obtained for the inhomogeneous equation will be presented for the case when L is a strictly elliptic second order divergence form operator on a rough boundary (Lipschitz) domain.
Probabilistic Dynamic Belief Logic for Image and Reputation
Authors: Isaac Pinyol, Jordi Sabater-Mir, Pilar Dellunde
Venue: Proceeding of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence (2008)

Since electronic and open environments became a reality, computational trust and reputation models have attracted increasing interest in the field of multi-agent systems (MAS). Some of them are based on cognitive theories of reputation that require cognitive agents to display all their potential. One of them is Repage, a computational system based on a cognitive theory of reputation that focuses on the study of two important concepts: Image and Reputation. The possible integration of these Repage predicates into a cognitive agent architecture, like the well-known Belief, Desire, Intention (BDI) approach implies the definition of these two concepts as mental states, as a set of beliefs. In this paper, we specify a belief logic that captures the necessary elements to express Image and Reputation and we study their interplay by analyzing a classical definition of trust on information sources.
Mass data exploration in oncology: An information synthesis approach
Authors: Julie Bourbeillon, Catherine Garbay, Françoise Giroud
Venue: Journal of Biomedical Informatics (2009)

New technologies and equipment allow for mass treatment of samples and research teams share acquired data on an always larger scale. In this context scientists are facing a major data exploitation problem. More precisely, using these data sets through data mining tools or introducing them in a classical experimental approach require a preliminary understanding of the information space, in order to direct the process. But acquiring this grasp on the data is a complex activity, which is seldom supported by current software tools. The goal of this paper is to introduce a solution to this scientific data grasp problem. Illustrated in the Tissue MicroArrays application domain, the proposal is based on the synthesis notion, which is inspired by Information Retrieval paradigms. The envisioned synthesis model gives a central role to the study the researcher wants to conduct, through the task notion. It allows for the implementation of a task-oriented Information Retrieval prototype system. Cases studies and user studies were used to validate this prototype system. It opens interesting prospects for the extension of the model or extensions towards other application domains.
Enabling Adoption of STEP Standards Through the Use of Popular Technologies
Authors: Carlos Agostinho, Marco Delgado, Adolfo Steiger-Garção, Ricardo Jardim-Gonçalves
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

With the advent of globalization, enterprises, especially Small and Medium Enterprises (SMEs), need to be efficient, effective and to embrace innovation. These characteristics are vital in order to face the global market environment, which raises the need for collaboration and interoperability in a more demanding and competitive industrial scenario. Interoperability and standardization are proven approaches to leverage collaboration and help establishing business networks, increasing competitiveness of organizations. However, some of these organizations have been experiencing some problems when trying to adopt one of the most important standards for the exchange of product data, the STEP (ISO10303). These problems are due to the poor software support and usage of complex technologies. This paper proposes as a solution, a framework for the harmonization of STEP conceptual models and knowledge with other standard technologies commonly adopted by today's organizations. The results presented in this paper has been supported and validated in the scope of the some European/International industrial research projects like the IMS SMART-fm (www.smart-fm.funstep.org), Athena-IP (www.athena-ip.org), and InterOp (www.interop-noe.org).
Supporting E-Learning System with Modified Bayesian Rough Set Model
Authors: Ayad R. Abbas, Liu Juan
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

The increasing development of Internet, especially Web-based learning is one of the most important issues. In this paper, a new application on Bayesian Rough Set (BRS) model for give information about learner performance is formulated. To enhance the precision of original rough set and to deal with both two decision classes and multi decision classes, we modify BRS model based on Bayesian Confirmation Measures (BCM). The experimental results are compared with that got by other methods. The quality of the proposed BRS model can be evaluated using discriminant index of decision making, which is suitable for providing appropriate decision rules to the learners with high discriminant index.
A Geometric PDE for Interpolation of M-Channel Data
Authors: Frank Lenzen, Otmar Scherzer
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

We propose a partial differential equation to be used for interpolating M-channel data, such as digital color images. This equation is derived via a semi-group from a variational regularization method for minimizing displacement errors. For actual image interpolation, the solution of the PDE is projected onto a space of functions satisfying interpolation constraints. A comparison of the test results with standard and state-of-the-art interpolation algorithms shows the competitiveness of this approach.
Real time determination of sensor node location in a wireless sensor network using particle swarm optimization
Authors: H. A. Nguyen, K S. Low, H. Guo
Venue: Proceedings of the 10th WSEAS international conference on evolutionary computing (2009)

In this paper, we investigate a localization system that consists of unknown emitter nodes in a wireless sensor network (WSN) with four anchor nodes that have known locations. It is assumed that the only available information to the system is the received signal strength indicators (RSSI) of the RF signals that are in practice difficult to be accurately measured. To estimate the unknown node position, particle swarm optimization (PSO) approach is first utilized to estimate the multipath model of the transmission channel. The estimated channel model is then used together with the PSO to perform estimation of the sensor node position. Both simulation and experimental results of the proposed approach are presented and shown to be better than previously reported results.
Knuth relations for the hyperoctahedral groups
Authors: Thomas Pietraho
Venue: Journal of Algebraic Combinatorics: An International Journal (2009)

C. Bonnafé, M. Geck, L. Iancu, and T. Lam have conjectured a description of Kazhdan-Lusztig cells in unequal parameter Hecke algebras of type B which is based on domino tableaux of arbitrary rank. In the integer case, this generalizes the work of D. Garfinkle. We adapt her methods and construct a family of operators which generate the equivalence classes on pairs of arbitrary rank domino tableaux described in the above conjecture.
A study of process arrival patterns for MPI collective operations
Authors: Ahmad Faraj, Pitch Patarasuk, Xin Yuan
Venue: International Journal of Parallel Programming (2008)

Process arrival pattern, which denotes the timing when different processes arrive at an MPI collective operation, can have a significant impact on the performance of the operation. In this work, we characterize the process arrival patterns in a set of MPI programs on two common cluster platforms, use a micro-benchmark to study the process arrival patterns in MPI programs with balanced loads, and investigate the impacts of different process arrival patterns on collective algorithms. Our results show that (1) the differences between the times when different processes arrive at a collective operation are usually sufficiently large to affect the performance; (2) application developers in general cannot effectively control the process arrival patterns in their MPT programs in the cluster environment: balancing loads at the application level does not balance the process arrival patterns; and (3) the performance of collective communication algorithms is sensitive to process arrival patterns. These results indicate that process arrival pattern is an important factor that must be taken into consideration in developing and optimizing MPI collective routines. We propose a scheme that achieves high performance with different process arrival patterns, and demonstrate that by explicitly considering process arrival pattern, more efficient MPI collective routines than the current ones can be obtained.