ppxscal/embedding_network huggingface dataset:
A Numerical Study on the Enhancement of Heat Transfer by Pressure Distributions in Acoustic Fields
Authors: Y. K. Oh, H. D. Yang
Venue: Journal of Visualization (2005)

The enhancement of heat transfer in a cavity was investigated in the absence of and in the presence of acoustic streaming induced by ultrasonic waves. The present study provides the experimental and numerical results of heat transfer in the acoustic fields. The enhancement of heat transfer was experimentally investigated in the presence of acoustic streaming and was compared with the profiles of acoustic pressure calculated by the numerical analysis. A coupled finite element-boundary element method (FE-BEM) was applied for a numerical analysis. Experimental and numerical studies clearly show that pressure variations are closely related to the enhancement of heat transfer in the acoustic fields.
The Web Service Modeling Toolkit - An Integrated Development Environment for Semantic Web Services
Authors: Mick Kerrigan, Adrian Mocan, Martin Tanler, Dieter Fensel
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

The time of engineers is a precious commodity. This is especially true for engineers of semantic descriptions, who need to be highly skilled in conceptual modeling, a skill which will be in high demand as Semantic Web technologies are adopted by industry. Within the software engineering community Integrated Development Environments (IDEs) like the Eclipse Java Development Toolkit and NetBeans have proved to increase the productivity of engineers by bringing together tools to help engineers with their everyday tasks. This paper motivates the need for such an IDE for the Semantic Web and in particular describes the Web Service Modeling Toolkit (WSMT), an Integrated Development Environment for Semantic Web Services through the WSMO paradigm.
Evaluating a Simulated Student Using Real Students Data for Training and Testing$^{\thanks{The research presented in this paper is supported by National Science Foundation Award No. REC-0537198.}}$
Authors: Noboru Matsuda, William W. Cohen, Jonathan Sewall, Gustavo Lacerda, Kenneth R. Koedinger
Venue: Proceedings of the 11th international conference on User Modeling (2007)

SimStudent is a machine-learning agent that learns cognitive skills by demonstration. It was originally developed as a building block of the Cognitive Tutor Authoring Tools (CTAT), so that the authors do not have to build a cognitive model by hand, but instead simply demonstrate solutions for SimStudent to automatically generate a cognitive model. The SimStudent technology could then be used to model human students' performance as well. To evaluate the applicability of SimStudent as a tool for modeling real students, we applied SimStudent to a genuine learning log gathered from classroom experiments with the Algebra I Cognitive Tutor. Such data can be seen as the human students' "demonstrations" of how to solve problems. The results from an empirical study show that SimStudent can indeed model human students' performance. After training on 20 problems solved by a group of human students, a cognitive model generated by SimStudent explained 82% of the problem-solving steps performed correctly by another group of human students.
An Improved Differential Evolution with Local Search for Constrained Layout Optimization of Satellite Module
Authors: Wang Chen, Yan-Jun Shi, Hong-Fei Teng
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

This paper proposes an improved differential evolution algorithm (called by DEG hereinafter) to tackle a kind of combinatorial optimization problem, i.e., constrained component layout optimization of satellite module. DEG combined local search with standard DE by employing the Gauss mutation operator from genetic algorithm, aiming to make random micro-perturbations to the location of components for obtaining a better layout scheme. The experimental results showed that the proposed DEG outperformed the standard DE and Genetic algorithm on layout design of simplified satellite module.
Smart support functions for sequential pattern mining
Authors: Dunren Che, Wei Zheng
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

In real applications, transaction data typically contain quantitative attributes. Existing approaches and algorithms proposed for sequential pattern mining such as AprioriAll often assume Boolean attributes (i.e., quantitative values are simply interpreted/transformed as Boolean values). This article addresses the impact of varied quantitative attributes in sequential pattern mining. More specifically, we define alternate smart support functions for computing the support measure of candidate sequential patterns. A noticeable advantage of this work is that the proposed smart support functions can be smoothly integrated into the framework of existing sequential pattern mining algorithms. In the discussion of this article, we assume adoption of the well-known AprioriAll algorithm and discuss the incorporation of the proposed smart support functions into this framework. The expected mining results are believed better reflecting the particular interests of different user groups and thus are more satisfactory to the intended users.
Beam search heuristics for the single machine early/tardy scheduling problem with no machine idle time
Authors: Jorge M. S. Valente
Venue: Computers and Industrial Engineering (2008)

In this paper, we present beam search heuristics for the single machine early/tardy scheduling problem with job-independent penalties, and no machine idle time. These heuristics include priority and detailed classic beam search algorithms, as well as filtered and recovering procedures. Three dispatching rules are considered as evaluation functions, in order to analyse the effect of different rules on the performance of the beam search heuristics. The computational results show that the performance of the beam search procedures does improve with the quality of the dispatching rule. The detailed and recovering algorithms clearly outperform the best existing heuristic, and the improvement is particularly higher for the more difficult instances. The detailed beam search algorithm provides the best performance, and is recommended for small to medium size instances. For larger instances, however, this algorithm requires excessive computation times. The recovering beam search procedure is computationally more efficient, and is then the heuristic of choice for medium to large instances.
Engineering experience with the SEAC
Authors: Ralph J. Slutz
Venue: Papers and discussions presented at the Dec. 10-12, 1951, joint AIEE-IRE computer conference: Review of electronic digital computers (1951)

From the time of its early planning phases the SEAC program at the National Bureau of Standards has had a dual purpose. One objective has been, of course, the provision of a tool for use in the solution of problems in calculation, but a second and equally important aspect is the use of this equipment to provide experience with which better tools can be designed in the future. Thus about one-third of SEAC's time during the past year has been used for the testing out of new equipment in order to obtain design experience for further development.
BLB: A Persuasive and Interactive Installation Designed to Improve Well-Being
Authors: Connie Golsteijn, Elise Hoven, Sijme Geurts, Max Eichenbrenner, Christ Leest, Sanne Hurk, Yih Shun Ling
Venue: Proceedings of the 3rd international conference on Persuasive Technology (2008)

Well-being is a broad subject, which is described in this paper as: a personal balance of mental, social and physical being, influenced by life circumstances and life factors. These factors include emotions, engagement, life satisfaction, intentional activities and social network. The project described in this paper aims at improving well-being through the design of a persuasive and interactive installation for the home environment. After the investigation of well-being by means of a literature study, cultural probes and questionnaires, a concept was developed. This paper describes the design, implementation and evaluation of this concept. `BLB', as it is called, encourages its users to seize the moment in order to increase their well-being.
Positivity, posynomials and tile size selection
Authors: Lakshminarayanan Renganarayana, Sanjay Rajopadhye
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

Tiling is a widely used loop transformation for exposing/exploiting parallelism and data locality. Effective use of tiling requires selection and tuning of the tile sizes. This is usually achieved by developing cost models that characterize the performance of the tiled program as a function of tile sizes. All previous approaches to tile size selection (TSS) are cost model specific. Due to this they are neither extensible (e.g., to richer program classes/newer architectures) nor scalable (e.g., to multiple levels of tiling). This paper identifies positivity as a fundamental property shared by the functions and parameters commonly used in TSS models. We show how this positivity can be used as a basis to derive a TSS framework which is both efficient and scalable. We also show that almost all TSS models proposed in the literature (including those used in production compilers and auto-tuners) can be reduced to our framework.
A Run-Time Efficient Implementation of Compressed Pattern Matching Automata
Authors: Tetsuya Matsumoto, Kazuhito Hagio, Masayuki Takeda
Venue: Proceedings of the 13th international conference on Implementation and Applications of Automata (2008)

We present a run-time efficient implementation of automata for compressed pattern matching (CPM), where a text is given as a truncation-free collage system $\langle{\mathcal D},{\mathcal S}\rangle$ such that variable sequence $\mathcal S$ is encoded by any prefix code. We experimentally show that a combination of recursive-pairing compression and byte-oriented Huffman coding allows both a high compression ratio and a high speed CPM.
A passport recognition and face verification using enhanced fuzzy ART based RBF network and PCA algorithm
Authors: Kwang-Baek Kim, Sungshin Kim
Venue: Neurocomputing (2008)

In this paper, passport recognition and face verification methods which can automatically recognize passport codes and discriminate forgery passports to improve efficiency and systematic control of immigration management are proposed. Adjusting the slant is very important for recognition of characters and face verification since slanted passport images can bring various unwanted effects to the recognition of individual codes and faces. Therefore, after smearing the passport image, the longest extracted string of characters is selected. The angle adjustment can be conducted by using the slant of the straight and horizontal line that connects the center of thickness between left and right parts of the string. Extracting passport codes is done by Sobel operator, horizontal smearing, and 8-neighborhood contour tracking algorithm. The string of codes can be transformed into binary format by applying repeating binary method to the area of the extracted passport code strings. The proposed radial basis function (RBF) network is applied to the middle layer of RBF network by using the fuzzy logic connection operator and proposing the enhanced fuzzy adaptive resonance theory (ART) algorithm that dynamically controls the vigilance parameter. After several tests using a forged passport and the passport with slanted images, the proposed method was proven to be effective in recognizing passport codes and verifying facial images.
Annotating Relationships Between Multiple Mixed-Media Digital Objects by Extending Annotea
Authors: Ronald Schroeter, Jane Hunter, Andrew Newman
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

Annotea provides an annotation protocol to support collaborative Semantic Web-based annotation of digital resources accessible through the Web. It provides a model whereby a user may attach supplementary information to a resource or part of a resource in the form of: either a simple textual comment; a hyperlink to another web page; a local file; or a semantic tag extracted from a formal ontology and controlled vocabulary. Hence, annotations can be used to attach subjective notes, comments, rankings, queries or tags to enable semantic reasoning across web resources. More recently, tabbed browsers and specific annotation tools, allow users to view several resources (e.g., images, video, audio, text, HTML, PDF) simultaneously in order to carry out side-by-side comparisons. In such scenarios, users frequently want to be able to create and annotate a link or relationship between two or more objects or between segments within those objects. For example, a user might want to create a link between a scene in an original film and the corresponding scene in a remake and attach an annotation to that link. Based on past experiences gained from implementing Annotea within different communities in order to enable knowledge capture, this paper describes and compares alternative ways in which the Annotea Schema may be extended for the purpose of annotating links between multiple resources (or segments of resources). It concludes by identifying and recommending an optimum approach which will enhance the power, flexibility and applicability of Annotea in many domains.
On Proofs and Rule of Multiplication in Fuzzy Attribute Logic
Authors: Radim Belohlavek, Vilem Vychodil
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

The paper develops fuzzy attribute logic, i.e. a logic for reasoning about formulas of the form $A\Rightarrow B$ where A and B are fuzzy sets of attributes. A formula $A\Rightarrow B$ represents a dependency which is true in a data table with fuzzy attributes iff each object having all attributes from A has also all attributes from B, membership degrees in A and B playing a role of thresholds. We study axiomatic systems of fuzzy attribute logic which result by adding a single deduction rule, called a rule of multiplication, to an ordinary system of deduction rules complete w.r.t. bivalent semantics, i.e. to well-known Armstrong axioms. In this paper, we concentrate on the rule of multiplication and its role in fuzzy attribute logic. We show some advantageous properties of the rule of multiplication. In addition, we show that these properties enable us to reduce selected problems concerning proofs in fuzzy attribute logic to the corresponding problems in the ordinary case. As an example, we discuss the problem of normalization of proofs and present, in the setting of fuzzy attribute logic, a counterpart to a well-known theorem from database theory saying that each proof can be transformed to a so-called RAP-sequence.
Regular Decompositions
Authors: Guillaume Moroz
Venue: Computer Mathematics: 8th Asian Symposium, ASCM 2007, Singapore, December 15-17, 2007. Revised and Invited Papers (2008)

We introduce the notion of regular decomposition of an ideal and present a first algorithm to compute it. Designed to avoid generic perturbations and eliminations of variables, our algorithm seems to have a good behaviour with respect to the sparsity of the input system. Beside, the properties of the regular decompositions allow us to deduce new algorithms for the computation of the radical and the weak equidimensional decomposition of an ideal. A first implementation shows promising results.
Value-based predicate filtering of XML documents
Authors: Joonho Kwon, Praveen Rao, Bongki Moon, Sukho Lee
Venue: Data Knowledge Engineering (2008)

In recent years, publish-subscribe systems based on XML filtering have received much attention in ubiquitous computing environments and Internet applications. The main challenge is to process a large number of content against millions of user subscriptions. Several XML filtering systems focus on the efficient processing of structural matching of user subscriptions represented as XPath twig patterns. However, existing techniques provide limited or no support for twig patterns that contain various operators in the value-based predicates. In this paper, we present the pFiST system that filters XML documents by transforming twig patterns into sequences based on Prufer's method. This sequencing idea for XML filtering was first demonstrated by FiST [J. Kwon, P. Rao, B. Moon, S. Lee, FiST: scalable XML document filtering by sequencing twig patterns, in: Proceedings of the 31st VLDB Conference, Trondheim, Norway, 2005, pp. 217-228]. The focus of pFiST is to support value-based predicates in twig patterns in addition to matching their structure. The pFiST system supports equality and non-equality operators, and in addition can handle logical operators such as AND and OR in the value-based predicates. Extensive experimental results show that pFiST provides good performance over data sets with different characteristics.
Visualisation to Aid Biodiversity Studies through Accurate Taxonomic Reconciliation
Authors: Martin Graham, Paul Craig, Jessie Kennedy
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

All aspects of organismal biology rely on the accurate identification of specimens described and observed. This is particularly important for ecological surveys of biodiversity, where organisms must be identified and labelled, both for the purposes of the original research, but also to allow reinterpretation or reuse of collected data by subsequent research projects. Yet it is now clear that biological names in isolation are unsuitable as unique identifiers for organisms. Much modern research in ecology is based on the integration (and re-use) of multiple datasets which are inherently complex, reflecting any of the many spatial and temporal environmental factors and organismal interactions that contribute to a given ecosystem. We describe visualization tools that aid in the process of building concept relations between related classifications and then in understanding the effects of using these relations to match across sets of classifications.
Graphs from Search Engine Queries
Authors: Ricardo Baeza-Yates
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

Server logs of search engines store traces of queries submitted by users, which include queries themselves along with Web pages selected in their answers. Here we describe several graph-based relations among queries and many applications where these graphs could be used.
A new local PCA-SOM algorithm
Authors: Dong Huang, Zhang Yi, Xiaorong Pu
Venue: Neurocomputing (2008)

This paper proposes a local PCA-SOM algorithm. The new competition measure is computational efficient, and implicitly incorporates the Mahalanobis distance and the reconstruction error. The matrix inversion or PCA decomposition for each data input is not needed as compared to the previous models. Moreover, the local data distribution is completely stored in the covariance matrix instead of the pre-defined numbers of the principal components. Thus, no priori information of the optimal principal subspace is required. Experiments on both the synthesis data and a pattern learning task are carried out to show the performance of the proposed method.
AntLib v1.0: A Generic C++ Framework for Ant Colony Optimization
Authors: Francisco Javier Diego Martín, José Ángel González Manteca, Ruth Carrasco-Gallego, Javier Carrasco Arias
Venue: Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence (2008)

This paper introduces AntLib, an Ant Colony Optimization (ACO) framework. C++ developed; it is a generic framework that can be applied with almost no adaptations to any combinatorial optimization problem. AntLib is a reusable object oriented framework, based on several well known design patterns [2].
An Algorithm of Constrained Spatial Association Rules Based on Binary
Authors: Gang Fang, Zukuan Wei, Qian Yin
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

An algorithm of constrained association rules mining was presented in order to search for some items expected by people. Since some presented algorithms of association rules mining based on binary are complicated to generate frequent candidate itemsets, they may pay out heavy cost when these algorithms are used to extract constrained spatial association rules. And so this paper proposes an algorithm of constrained spatial association rules based on binary, the algorithm is suitable for mining constrained association among some different spatial objects under the same spatial pattern, which uses the way of ascending value to generates frequent candidate itemsets and digital character to reduce the number of scanned transaction in order to improve the efficiency. The experiment indicates that the algorithm is faster and more efficient than theses presented algorithms based on binary when mining constrained spatial association rules from spatial database.
Segmentation Techniques for Automatic Region Extraction: An Application to Aphasia Rehabilitation
Authors: M. G. Albanesi, S. Panzarasa, B. Cattani, S. Dezza, M. Maggi, S. Quaglini
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

We describe a system that facilitates speech therapists to administer cognitive rehabilitation exercises and to evaluate treatment outcomes. We started by augmenting a commercial tool with a more user-friendly interface, meeting the needs of the healthcare professionals involved. Then we integrated, into the same tool, a new type of exercise, that is particularly patient-tailored, being based on the recognition of familiar images within a picture (such as a relative, a domestic animal, a home object, etc). Segmentation techniques are used to elaborate an input picture and individuate areas including interesting objects, that will be semi-automatically linked to text and sound. The picture and associated information are then stored in the system database and may be subsequently used as objects for the new exercise. Any number of images may be elaborated, personalised and stored for each patient. The performance has been tested on voluntary subjects with good results.
Markov models for application behavior analysis
Authors: Geoffrey Mazeroff
Venue: Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead (2008)

Given the pervasive nature of malicious mobile code (viruses, worms, etc.), developing statistical/structural models of application execution is of considerable importance in the domain of cyber security. This work describes the inference of Markov models based on system call sequences realized by Windows XP applications: discrete-parameter Markov chains for the sequential nature of the system calls, and continuous-parameter Markov chains for the inter-arrival times between system calls. Both types of Markov chains are inferred using benign application data, and thus serve as models of benign application behavior. The goal is to classify new, unobserved system call sequences essentially as "self" or "non-self" based on the amount of deviation such sequences exhibit from the inferred models. The techniques of inference and classification can be applied to cyber security by detecting anomalous application behavior, exhibited by either malicious mobile code or unvetted benign applications.