ppxscal/embedding_network huggingface dataset:
Technical Section: Modeling and 3D object reconstruction by implicitly defined surfaces with sharp features
Authors: Xinghua Song, Bert Jüttler
Venue: Computers and Graphics (2009)

We propose a new method for describing sharp features (i.e., edges and vertices) of implicitly defined surfaces. We consider an initial implicitly defined surface, which is represented as the zero set of a C^1 smooth scalar field with non-vanishing gradients. In order to represent sharp edges and vertices, this surface is augmented by adding new types of implicit representations, called edge descriptors and vertex descriptors. They are defined with the help of the distance field of edge curves. In our implementation, we use circular splines to describe these edge curves, since they support a fast and non-iterative closest point computation. After adding the edge and vertex descriptors to the initial scalar field, the zero set of the augmented function contains the sharp features. We apply the new representation to surface modeling by implicitly defined surfaces with sharp features and to object reconstruction. In the latter case we describe an algorithm for detecting the sharp curves and vertices of a shape which is given by an unorganized point cloud, which are then approximated by circular splines, in order to define the edge and vertex descriptors.
Practical Numerical Simulations of Two-Phase Flow and Heat Transfer Phenomena in a Thermosyphon for Design and Development
Authors: Zheshu Ma, Ali Turan, Shengmin Guo
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

Two-phase closed thermosyphons are widely-used in various energy intensive industries including chemical, transportation and other industries for their inherently high heat transfer efficiency, simple construction and reliable operational performance. However, the performance parameters of two-phase closed thermosyphons including the distribution of internal pressure, steam and liquid phase mass fractions, velocity and wall temperatures are obtained primarily via experimental investigations. In this paper numerical methods are discussed and a two-fluid model is employed to describe the two-phase flow and heat transfer processes in a two-phase closed thermosyphon. The IPSA (Inter Phase Slip Algorithm) algorithm is employed to solve the coupled interactions of steam and liquid phases along the phase interface. Flow patterns and distribution of parameters under different conditions are predicted with numerical results agreeing well for the most part with experimental results. Thus, the numerical method and solution procedures are claimed to be of practical utility and can in essence be used profitably to simulate flow and heat transfer phenomena in thermosyphons and other types of heat pipes.
How Technology Can Help Reducing the Legal Burden
Authors: Tom van Engers, Ron van Gog, Arian Jacobs
Venue: Proceeding of the 2005 conference on Legal Knowledge and Information Systems: JURIX 2005: The Eighteenth Annual Conference (2005)

This short paper explains how relative simple technology can help governments to reduce the legal burden.
Knowledge Audit on Special Children Communities
Authors: Aida Suzana Sukiam, Azizah Abdul Rahman, Wardah Zainal Abidin
Venue: Knowledge Acquisition: Approaches, Algorithms and Applications: Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, Hanoi, Vietnam, December 15-16, 2008, Revised Selected Papers (2009)

This paper reports on how knowledge audit analysis was conducted for special children (SC) communities in Malaysia context. The purpose of the knowledge audit is to determine the knowledge requirement of SC communities which may reveal the required, available and missing knowledge and the person involved related to SC. Four communities of practice (CoPs) have been identified namely Parents, Educators, Medical Experts and Researchers. The knowledge audit has been conducted in four phases. There are Knowledge Needs Analysis, Knowledge Inventory Analysis, Knowledge Flows Analysis and Knowledge Mapping. Questionnaires and interviews were conducted as knowledge audit tools for facilitating the collection of data, information and evident. In order to represent the knowledge audit results, matrices presentation is used. These representations help in tracing knowledge and verify the results with the CoPs more clearly. The result shows that knowledge audit yields a number of benefits that include the missing gap between required and available knowledge. The requirement can be used to develop a one stop center for SC communities to communicate among other CoPs. Subsequently, recommendations can be derived for better managing of the knowledge.
Quasi-physical algorithm of an off-lattice model for protein folding problem
Authors: Jing-Fa Liu, Wen-Qi Huang
Venue: Journal of Computer Science and Technology (2007)

Protein folding problem is one of the most prominent problems of bioinformatics. In this paper, we study a three-dimensional off-lattice protein AB model with two species of monomers, hydrophobic and hydrophilic, and present a heuristic quasi-physical algorithm. By elaborately simulating the movement of the smooth elastic balls in the physical world, the algorithm finds low-energy configurations for a given monomer chain. A subsequent "off-trap" strategy is proposed to trigger a jump for a stuck situation in order to get out of local minima. The methods have been tested in the off-lattice AB model. The computational results show promising performance. For all sequences with 13 to 55 monomers, the algorithm finds states with lower energy than previously proposed putative ground states. Furthermore, for the sequences with 21, 34 and 55 monomers, new putative ground states are found, which are different from those given in present literature.
Direct kernel neighborhood discriminant analysis for face recognition
Authors: Haifeng Hu, Ping Zhang, Zhengming Ma
Venue: Pattern Recognition Letters (2009)

A nonlinear face recognition technique based on neighborhood preserving discriminant analysis (NPDA) is proposed. The kernel trick is adopted to allow the efficient computation of local Fisher discriminant in high-dimensional feature space. Moreover, a direct solution for obtaining the optimal feature vectors in feature space is presented which can preserve the most discriminative information. The proposed algorithm is evaluated on the UMIST database, the ORL database and the FERET database by using six different methods. Experiments show that consistent and promising results are obtained.
Enriching Solution Space for Robustness in an Intelligent Tutoring System
Authors: Hameedullah Kazi, Peter Haddawy, Siriwan Suebnukarn
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

Intelligent tutoring systems assist medical faculty in training and equipping students with the required clinical reasoning skills. Plausible student solutions to a given problem are rejected by tutoring systems as being incorrect, if they do not match a specific solution accepted by the tutoring system. This leads to brittleness in evaluating student solutions. In this paper we describe a combination of knowledge base expansion and exploitation of existing knowledge structure to enhance robustness in an intelligent tutoring system for medical problem-based learning using UMLS. We present a tutoring system that enriches the solution space by collating different plausible solutions and exploiting the knowledge structure in UMLS to offer students a broader scope of reasoning.
Robust Biometric Key Extraction Based on Iris Cryptosystem
Authors: Long Zhang, Zhenan Sun, Tieniu Tan, Shungeng Hu
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Biometric cryptosystem can not only provide an efficient mechanism for template protection, but also facilitate cryptographic key management, thus becomes a promising direction in information security field. In this paper, we propose a robust key extraction approach which consists of concatenated coding scheme and bit masking scheme based on iris database. The concatenated coding scheme that combines Reed-Solomon code and convolutional code is proposed so that much longer keys can be extracted from the iris data, while the bit masking scheme is proposed to minimize and randomize the errors occur in the iris codes, making the error pattern more suitable for the coding scheme. The experiment results show that the system can achieve a FRR of 0.52% with the key length of 938 bits.
A comparison of parallel gaussian elimination solvers for the computation of electrochemical battery models on the cell processor
Authors: John L. Wyatt,  Jr.
Venue:  (2008)

The rising cost of fossil fuels, together with a push for more eco-friendly methods of transportation, has increased interest in and demand for electrically powered or assisted vehicles. The majority of these electric or hybrid electric vehicles will be, for the foreseeable future, powered by batteries. One of the major problems with batteries is their aging. For batteries, aging means that the maximum charge they can store decreases as number of charge/discharge cycles increases. Aging also means that after a certain number of charge/discharge cycles, the battery will fail. In lead-acid batteries, one of the major phenomenon that promotes battery failure is the development of a non-uniform concentration gradient of electrolyte along the electrodes' height. This phenomenon is known as electrolyte stratification. This thesis develops a simple two-level circuit model that can be used to model electrolyte stratification. The two-level circuit model is justified experimentally using digital Mach-Zehnder interferometry and is explained theoretically by means of two different electrochemical battery models. The experiments show how the usage of the electrode varies along its height while the simulations indicate that the high resistivity of the lead dioxide electrode plays a major role in the development of a stratified electrolyte. Finally, computational issues associated with the computation of a sophisticated two dimensional electrochemical battery model on the multicore Cell Broadband Engine processor are addressed in detail. In particular, three different banded parallel Gaussian elimination solvers are developed and compared. These three solvers vividly illustrate how performance achieved on the new multicore processors is strongly dependent on the algorithm used. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Improving Chinese Language Competency of Ethnic Chinese Pupils with Story Building and Multi-User Virtual Environment --A Case Study
Authors: Yin Mei Wong
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

This paper reports an exploratory case study on the effects of story building and Multi-User Virtual Environment (MUVE) on elementary pupils learning of Chinese language. Preliminary analysis of three pupils shows evidence of improvement in pupils' language competency and thinking ability. The pupils seemed to learn through mimicking words and phrases that caught their attention during the interaction with their peers. Further studies are needed to uncover other mechanisms through which learning in MUVE occurs and to assess the generalisability of the findings.
Non-linear turbulence models for multiphase recirculating free-surface flow over stepped spillways
Authors: Amarin Tongkratoke, Chaiyuth Chinnarasri, Adichai Pornprommin, Pramote Dechaumphai, Varangrat Juntasaro
Venue: International Journal of Computational Fluid Dynamics (2009)

The flow over a stepped spillway is free surface, multiphase and turbulent. Moreover, a recirculation region occurs at each step of the spillway. The flow characteristic is hence complicated and difficult to predict. In previous work on stepped spillways (Chen et al. Journal of Hydraulic Engineering, ASCE, 128 (7), 683-688 and Xiangju et al. Science in China Series E: Technological Sciences, 49 (3), 674-684), only the linear turbulence model was applied which gave low accuracy. Furthermore, there are still no optimised model constants for this kind of flow. The present work therefore aims to apply the large eddy simulation (LES), the non-linear and the modified non-linear turbulence models to simulate the flow over the spillways with various slopes and step heights. It is found that the modified model is able to predict the flow close to the LES but requires less computational time by a factor of up to 4. Moreover, the modified model gives higher accuracy than the LES for the cases of the spillways with higher slopes and step heights.
An Introduction to Chemoinformatics
Authors: Andrew R. Leach, Valerie J. Gillet
Venue:  (2007)

Chemoinformatics draws upon techniques from many disciplines including computer science, mathematics, computational chemistry and data visualisation to tackle these problems. This, the first text written specifically for this field, aims to provide an introduction to the major techniques of chemoinformatics. The first part of the book deals with the representation of 2D and 3D molecular structures, the calculation of molecular descriptors and the construction of mathematical models. The second part describes other important topics including molecular similarity and diversity, the analysis of large data sets, virtual screening, and library design. Simple illustrative examples are used throughout to illustrate key concepts, supplemented with case studies from the literature. The book is aimed at graduate students, final-year undergraduates, and professional scientists. No prior knowledge is assumed other than a familiarity with chemistry and some basic mathematical concepts.
Image restoration with broken curve prediction
Authors: Hwei-Jen Lin, Chun-Wei Wang, Yuan-Chun Hsieh, Yang-Ta Kao
Venue: International Journal of Computational Vision and Robotics (2009)

In this paper, a new approach is presented for the restoration of missing or damaged portions of an image. The algorithm first locates several feature points on the boundary of the damaged region of a given image. Broken curves are then automatically predicted and reconstructed by using the B-spline functions. Finally, a method that combines the advantages of texture synthesis and image inpainting is applied to restore the remaining damaged portion. Several experimental results provided demonstrate the achievements of the proposed technique.
Innovative Learning and Unlearning
Authors: Di Fleming, Grace Lynch
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

The biggest barrier to innovation and change is not our resistance to learning something new, but rather unlearning what we think is the truth. Learning contexts should be diverse to evoke and capture student imagination. The pedagogy that underpins this process needs to focus on the development of students' ability to diagnose, simulate, problem solve, negotiate, construct, explore new ideas and exhibit their understanding.
Hardware-software implementation of lens model
Authors: Albert H. Titus, Alexander N. Cartwright
Venue:  (2008)

In this dissertation a decision making model called the Lens Model, is implemented with hardware-software hybrid&ndash;mode design. The system combines a software implementation of an Adaptive Linear Neuron (ADALINE) network to perform a part of the Lens Model computation, and hardware in the form of a specialized analog integrated circuit to complete the calculations. The majority of the research efforts have concentrated on the development of correlator chip, which calculates the correlation coefficient (consistence) between the predicted judgment and actual judgment. We propose three novel circuits for this: a Difference Squaring circuit, and Square Root circuit, and a Ratio circuit. The novel Difference Squaring circuit improves a previous design wherein the DC offset is cancelled, or removed. The Square Root circuit and the Ratio circuit are implemented with transistors working in the subthreshold mode with current exponential dependence on gate voltage. This learning chip has been fabricated using the CMOS 1.5&micro;m AMI ABN process available through the MOSIS integrated circuit fabrication service. The ADALINE (Adaptive Linear Neuron) was simulated using Matlab with a given set of profiles to produce a best-fitting network with least error between the estimated judgment and actual judgment. Different learning rates and training epochs were applied to monitor the effect of these factors. Total error between the estimated judgment and actual judgment is compared for these cases. The estimated judgment and actual judgment are stored and sent to the correlator chip via Labview to monitor the consistency between these two parameters after epochs of training. We present the experimental results obtained for the correlator block and the whole system. Test results show very good agreement between theory and measurements and thus indicate a successful design. The system can be used to determine the factors in individual performance in complex judgment tasks. This is the first time that the Lens Model was implemented in a hybrid software and hardware system.
A music context for teaching introductory computing
Authors: Ananya Misra, Douglas Blank, Deepak Kumar
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

We describe myro.chuck, a Python module for controlling music synthesis, and its applications to teaching introductory computer science. The module was built within the Myro framework using the ChucK programming language, and was used in an introductory computer science course combining robots, graphics and music. The results supported the value of music in engaging students and broadening their view of computer science.
Secure Telematic Applications for National Scale Projects - Volume 20 NATO Science for Peace and Security Series - D: Information and Communication Security ... and Communitcation Sercurity- Vol. 20)
Authors: J.-G. Fontaine, J.-G. Fontaine, M. Makhaniok
Venue:  (2009)

The NATO Advances Research Workshop (ARW) 'Secure Telematic Applications for National Scale Projects' is organized in the frame of the National Week of Information Technologies and Sixth International Congress 'Scientific and Methodological Facilitation of the Development of Informatization and the System of Scientific and Technical Information in the Republic of Belarus. Secure Telematic Applications in National and International Projects'. The participants of the event came to Minsk from all regions of Europe, as well as from Asia and Africa. Besides the general ARW topic, the participants also discussed the progress in the activity of the High Technologies Park, the creation of the corporate network of libraries of Belarus on the basis of the National Library of Belarus and the newest technologies of e-government. The presentations are also oriented on creation of the National Scientific and Research Computer Network of the Republic of Belarus on the basis of Academic Network BASNET. It is expected that the scientific and practical achievements of the forum will considerably influence both the development of the information technologies and their utilization for advantage of the national economy of Belarus and all participating countries.
Adaptive Algorithmic Hybrids for Human-Level Artificial Intelligence
Authors: Nicholas L. Cassimatis
Venue: Proceeding of the 2007 conference on Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the AGI Workshop 2006 (2007)

The goal of this chapter is to outline the attention machine computational framework designed to make a significant advance towards creating systems with human-level intelligence (HLI). This work is based on the hypotheses that: 1. most characteristics of human-level intelligence are exhibited by some existing algorithm, but that no single algorithm exhibits all of the characteristics and that 2. creating a system that does exhibit HLI requires adaptive hybrids of these algorithms. Attention machines enable algorithms to be executed as sequences of attention fixations that are executed using the same set of common functions and thus can integrate algorithms from many different subfields of artificial intelligence. These hybrids enable the strengths of each algorithm to compensate for the weaknesses of others so that the total system exhibits more intelligence than had previously been possible.
An mixed integer approach for optimizing production planning
Authors: Stefan Emet
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

In the present paper an optimization approach using Mixed Integer Nonlinear Programming (MINLP) techniques is presented. Different industrial applications are considered. The main issue in these problems are: which decisions should be made in order to both maximize the profits of the production and to minimize the production cycle time. Special Ordered Sets (SOS) are included in the models in order to allow the use of an efficient type of the Branch and Bound (BB) algorithm. A set of test problems are solved using the Extended Cutting Plane (ECP) method that has been proven efficient on many complex engineering problems. The obtained results are promising. It is shown that the production planning can be done efficiently so that the throughput is increased.
Applications of Data Mining in Constraint-based Intelligent Tutoring Systems
Authors: Karthik Nilakant, Antonija Mitrovic
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

The number of ITSs being used daily is growing steadily. Consequently, huge amounts of interaction data are available, but data analysis is still very laborious. This paper describes the use of data mining processes to investigate student interaction with a constraint-based tutor. We discuss how statistical analyses, information visualization and machine learning algorithms can be used to discover interesting patterns in data, and how the findings can be used to improve the system.
On burstiness-aware search for document sequences
Authors: Theodoros Lappas, Benjamin Arai, Manolis Platakis, Dimitrios Kotsakos, Dimitrios Gunopulos
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

As the number and size of large timestamped collections (e.g. sequences of digitized newspapers, periodicals, blogs) increase, the problem of efficiently indexing and searching such data becomes more important. Term burstiness has been extensively researched as a mechanism to address event detection in the context of such collections. In this paper, we explore how burstiness information can be further utilized to enhance the search process. We present a novel approach to model the burstiness of a term, using discrepancy theory concepts. This allows us to build a parameter-free, linear-time approach to identify the time intervals of maximum burstiness for a given term. Finally, we describe the first burstiness-driven search framework and thoroughly evaluate our approach in the context of different scenarios.