ppxscal/embedding_network huggingface dataset:
Microscopic polarization in ropes and films of aligned carbon nanotubes
Authors: Lasse Jensen, Anders L. Esbensen, Per-Olof Åstrand, Kurt V. Mikkelsen
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

The microscopic electric polarization in terms of the dipole-dipole polarizability and its second hyperpolarizability of aligned films and ropes of carbon nanotubes has been studied theoretically by a point-dipole interaction model. The results show clearly the influence of intertube interactions on the microscopic polarization demonstrating the sensitivity of the electronic structure of carbon nanotubes to the surroundings. Both the polarizability and the second hyperpolarizability are screened due to the intertube interactions and deviate substantially from an additive model. It is noted that both the polarizability and the second hyperpolarizability reach their minimum values around the van der Waals separation. In the rope arrangement the polarizability of a tube is reduced by 10% and the second hyperpolarizability by as much as 50% as compared to an unperturbed tube.
Sequence Labelling SVMs Trained in One Pass
Authors: Antoine Bordes, Nicolas Usunier, Léon Bottou
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

This paper proposes an online solver of the dual formulation of support vector machines for structured output spaces. We apply it to sequence labelling using the exact and greedy inference schemes. In both cases, the per-sequence training time is the same as a perceptron based on the same inference procedure, up to a small multiplicative constant. Comparing the two inference schemes, the greedy version is much faster. It is also amenable to higher order Markov assumptions and performs similarly on test. In comparison to existing algorithms, both versions match the accuracies of batch solvers that use exact inference after a single pass over the training examples.
A Test Data Compression Scheme for Reducing Power Based on OLELC and NBET
Authors: Jun Ma
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

A new test data compression scheme is introduced. This scheme encodes the test data provided by the core vendor, using a new and very effective compression scheme based on OLEL coding and neighboring bit-wise exclusive-or transform(OCNBET). Codeword is divided into two parts according to the position: odd bits and even bits. The odd bits of codeword are used to represent the length of runs and the even bits of codeword are used to represent whether a run is finished. Furthermore, a neighboring bit-wise exclusive-or transform is introduced to increase the probability of runs of 0s in the transformed data, so significant compression improvements and power efficient compared with the already known schemes are achieved. A simple architecture is proposed for decoding the compressed data on chip. Its hardware overhead is very low and comparable to that of the most efficient methods in the literature. Experimental results for the six largest ISCAS-89 benchmark circuits show that the proposed scheme is obviously better than the already known schemes in the aspects of compression ratio, power and the decompression structure.
Optimization of Ni-MH Battery Fast Charging in Electric Vehicles Using Dynamic Data Mining and ANFIS
Authors: Guifang Guo, Peng Xu, Zhifeng Bai, Shiqiong Zhou, Gang Xu, Binggang Cao
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Fast and efficient charging of Ni-MH battery is a problem which is difficult and often expensive to solve using conventional techniques. This study proposes a method that the integrated data mining algorithm and the Adaptive Network Fuzzy Inference Systems (ANFIS) for discovering the fast charging more efficiently and presenting it more concisely. Because the battery charging is a highly dynamic process, dynamic data mining technique is used for extracting of control rules for effective and fast battery process. The ideal fast charging current has been obtained. The result indicates that the integrated method of adaptive charging current has effectively improved charging efficiency and avoided overcharge and overheating.
Using the Simulated Annealing Algorithm for Multiagent Decision Making
Authors: Jiang Dawei, Wang Shiyuan
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

Coordination, as a key issue in fully cooperative multiagent systems, raises a number of challenges. A crucial one among them is to efficiently find the optimal joint action in an exponential joint action space. Variable elimination offers a viable solution to this problem. Using their algorithm, each agent can choose an optimal individual action resulting in the optimal behavior for the whole agents. However, the worst-case time complexity of this algorithm grows exponentially with the number of agents. Moreover, variable elimination can only report an answer when the whole algorithm terminates. Therefore, it is unsuitable in real-time systems. In this paper, we propose an anytime algorithm, called the simulated annealing algorithm, as an approximation alternative to variable elimination. We empirically show that our algorithm can compute nearly optimal results with a small fraction of the time that variable elimination takes to find the solution to the same coordination problem.
Effects of Salinity on Measurement of Water Volume Fraction and Correction Method Based on RBF Neural Networks
Authors: Chunguo Jing, Guangzhong Xing, Bin Liu, Qiuguo Bai
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The gamma ray dual modality densitometry was presented to measure salinity independent of water volume fraction in pipe flows. The simulation geometries of the dual modality densitometry were built using Monte Carlo software Geant4. Computer simulations were carried out with different types of salt and various salinity. The results show that type of salt and salinity have significant effects on the water volume fraction measured by dual modality densitometry. By means of measuring attenuation of transmitted and scattered radiation of dual modality densitometry, the information about the salinity changes can be obtained. But it is difficult to calculate WVF and salinity from dual modality densitometry models. The RBF neural networks were used to predict salinity and water volume fraction. The results show that the predicting values fit true values well. It was demonstrated that the water volume fraction measuring errors caused by salinity can be reduced by using RBF neural networks.
Development of Whole Breast Ultrasound Viewer and Automated Mass Detection System
Authors: Takeshi Hara, Daisuke Fukuoka, Yuji Ikedo, Etsuo Takada, Hiroshi Fujita, Tokiko Endo, Takako Morita
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

Ultrasonography is one of the most important methods for breast cancer diagnosis in Japan. In general, the ultrasonography using conventional handheld probe is operator-dependent, therefore, the quality of imaging depends on the operator technique, and the ultrasound images have less objectivity. Moreover, it is difficult for radiologists to interpret using comparison of left and right breast ultrasound images, comparison of previous ultrasound images, and double reading because ultrasound images are poor reproducibility and it is difficult to record entire breast images. In order to improve such problems, we have developed whole breast viewing system with computer-aided detection approach. All of the whole breast images were obtained by the AUS-1004 (ALOKA Co., Ltd., Japan). The detection performance was 80% with 3.8 FP marks per breast. The diagnostic effectiveness of the detection results and the possible browsing methods were implied.
Ranked-Listed or Categorized Results in IR: 2 Is Better Than 1
Authors: Zheng Zhu, Ingemar J. Cox, Mark Levene
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

In this paper we examine the performance of both ranked-listed and categorized results in the context of known-item search (target testing). Performance of known-item search is easy to quantify based on the number of examined documents and class descriptions. Results are reported on a subset of the Open Directory classification hierarchy, which enable us to control the error rate and investigate how performance degrades with error. Three types of simulated user model are identified together with the two operating scenarios of correct and incorrect classification. Extensive empirical testing reveals that in the ideal scenario, i.e. perfect classification by both human and machine, a category-based system significantly outperforms a ranked list for all but the best queries, i.e. queries for which the target document was initially retrieved in the top-5. When either human or machine error occurs, and the user performs a search strategy that is exclusively category based, then performance is much worse than for a ranked list. However, most interestingly, if the user follows a hybrid strategy of first looking in the expected category and then reverting to a ranked list if the target is absent, then performance can remain significantly better than for a ranked list, even with misclassification rates as high as 30%. We also observe that this hybrid strategy results in performance degradations that degrade gracefully with error rate.
An Application of NLP and Audiovisual Content Analysis for Integration of Multimodal Databases of Current Events
Authors: Alberto Messina
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

The nowadays explosion of pervasive services based on the Internet makes information about current events easy and rapidly available to any user. A critical point is concerned with the possibility for the users to have a comprehensive, trustworthy and multi-source informative dossiers on their events of interest. This paper presents a completely unsupervised architecture for the automatic detection and integration of informative sources about current events based on natural language processing and audiovisual content analysis. The system provides a multimodal RSS feed integrating both audiovisual and textual contributions.
Separation of Concerns and Consistent Integration in Requirements Modelling
Authors: Xin Chen, Zhiming Liu, Vladimir Mencl
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

Due to their increasing complexity, design of software systems is not becoming easier. Furthermore, modern applications ranging from enterprise to embedded systems require very high levels of correctness and dependability assurance. The most effective means to handle complexity is separation of concerns and incremental development, and assurance of correctness requires formal modelling and formal analysis. When separation of concerns splits the model into several parts, an important issue is to ensure consistency among these parts. We propose an approach supporting separation of concerns and consistent and incremental modelling of requirements.
Engineering rural development
Authors: Tapan S. Parikh
Venue: Communications of the ACM (2009)

Information systems enable rural development by increasing the accountability of nongovernmental organizations.
Using Stochastic Modeling for Texture Generation
Authors: Shinichiro Haruyama, Brian Barsky
Venue: IEEE Computer Graphics and Applications (1984)

A new computer graphics technique generates complicated random textures, like those found on natural objects. Requiring little data, it allows easy control of textural properties.
Talks on Quantum Computing
Authors: Sam Lomonaco
Venue: Proceedings of the 15th international workshop on Logic, Language, Information and Computation (2008)

This talk will give an overview of quantum computing in an intuitive and conceptual fashion. No prior knowledge of quantum mechanics will be assumed.The talk will begin with an introduction to the strange world of the quantum. Such concepts as quantum superposition, Heisenberg's uncertainty principle, the "collapse" of the wave function, and quantum entanglement (i.e., EPR pairs) are introduced. This part of the talk will also be interlaced with an introduction to Dirac notation, Hilbert spaces, unitary transformations, quantum measurement, and the density operator.Simple examples will be given to explain and to illustrate such concepts as quantum measurement, quantum teleportation, quantum dense coding, and the first quantum algorithm, i.e., the Deutsch-Jozsa algorithm.The PowerPoint slides for this talk will be posted at the URL: http://www. csee.umbc.edu/ lomonaco/Lectures.html
An XML Alternative for Performance and Security: ASN.1
Authors: Darren Mundy, David W. Chadwick
Venue: IT Professional (2004)

Performance tests of XML and ASN.1 found that signed complex XML messages can be up to 1,000 percent slower to decode than an equivalent ASN.1 message.
Autonomous jumping microrobots
Authors: Kristofer S. Pister
Venue:  (2007)

An autonomous jumping microrobot has been designed, and its mechanical components have been fabricated and tested. Millimeter-scale autonomous mobile microrobots have potential applications in mobile sensor networks as well as search and exploration tasks. However, mobility is difficult at this scale due to rugged surfaces, obstacles and locomotion efficiency. Jumping has been proposed as a locomotion method to overcome these challenges. The microrobot design has been divided into four components: energy storage, high work density actuators, power, and control. Like its biological inspiration, the flea, a jumping microrobot requires an energy storage mechanism to store energy and release it quickly to jump. Small leg lengths require large accelerations to reach takeoff velocities required to jump 10s of cm. Silicone micro rubber bands have been fabricated and demonstrated to store and quickly release enough energy for a 10 mg robot to jump 17 cm straight up. To stretch these micro rubber bands, electrostatic inchworm motors have been designed and fabricated to provide high forces and large displacements with low input power requirements. Three key design innovations have been used to improve the force density of these motor designs 37x over previous efforts. First, a pre-biasing actuator reduces initial electrostatic gaps below lithographic limits. Second, a toothless, friction-based clutch allows for variable stop sizes and single drive actuator motors. Third, silicon nitride has been added to reduce motor sire. Initial motor designs using these three new features have been fabricated and tested. Finally, several prototypes have been built to integrate and test the four robot components. A small-scale version of the full robot with previously fabricated solar cells and an off-the-shelf microcontroller driving a small inchworm motor has been demonstrated. Separately, an inchworm motor has been used to store energy in a micro rubber band for quick release. It is hoped that many of the design and fabrication ideas presented in this work can be used to make autonomous mobile microrobots a reality.
An Adaptive Michigan Approach PSO for Nearest Prototype Classification
Authors: Alejandro Cervantes, Inés Galván, Pedro Isasi
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

Nearest Prototype methods can be quite successful on many pattern classification problems. In these methods, a collection of prototypes has to be found that accurately represents the input patterns. The classifier then assigns classes based on the nearest prototype in this collection. In this paper we develop a new algorithm (called AMPSO), based on the Particle Swarm Optimization (PSO) algorithm, that can be used to find those prototypes. Each particle in a swarm represents a single prototype in the solution; the swarm evolves using modified PSO equations with both particle competition and cooperation. Experimentation includes an artificial problem and six common application problems from the UCI data sets. The results show that the AMPSO algorithm is able to find solutions with a reduced number of prototypes that classify data with comparable or better accuracy than the 1-NN classifier. The algorithm can also be compared or improves the results of many classical algorithms in each of those problems; and the results show that AMPSO also performs significantly better than any tested algorithm in one of the problems.
Global Exponential Stability and Periodicity of CNNs with Time-Varying Discrete and Distributed Delays
Authors: Shengle Fang, Minghui Jiang, Wenfang Fu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

In this paper, based on the Lyapunov stability analysis for functional differential equations, the problems of global exponential stability and periodic solutions for a class of cellular neural networks with time-varying delays and distributed delays are investigated. By constructing a new suitable Lyapunov functional, some simple sufficient conditions ensuring existence, uniqueness, global exponential stability of the equilibrium point and periodic oscillation of the networks are obtained, which are easy to check and apply in practice. In addition, an example is also given to illustrate the effectiveness of the theory.
Numerical and Statistical Methods for the Coarse-Graining of Many-Particle Stochastic Systems
Authors: Markos A. Katsoulakis, Petr Plecháč, Luc Rey-Bellet
Venue: Journal of Scientific Computing (2008)

In this article we discuss recent work on coarse-graining methods for microscopic stochastic lattice systems. We emphasize the numerical analysis of the schemes, focusing on error quantification as well as on the construction of improved algorithms capable of operating in wider parameter regimes. We also discuss adaptive coarse-graining schemes which have the capacity of automatically adjusting during the simulation if substantial deviations are detected in a suitable error indicator. The methods employed in the development and the analysis of the algorithms rely on a combination of statistical mechanics methods (renormalization and cluster expansions), statistical tools (reconstruction and importance sampling) and PDE-inspired analysis (a posteriori estimates). We also discuss the connections and extensions of our work on lattice systems to the coarse-graining of polymers.
A Simple Shadow Based Method for Camera Calibration
Authors: Imran N. Junejo
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

Using only shadow trajectories of stationary objects in a scene, we demonstrate that a camera can be calibrated robustly. We require at least two vertical objects to be visible in the image casting shadows on the ground plane. Using properties of these cast shadows, the horizon line (or the line at infinity) of the ground plane is robustly estimated. This leads to pole-polar constraints on the image of the absolute conic (IAC). We show that we require fewer images than the existing methods and demonstrate that our method performs well in presence of large noise. We perform experiments with synthetic data and real data captured from live webcams, demonstrating encouraging results.
Typed closure conversion preserves observational equivalence
Authors: Amal Ahmed, Matthias Blume
Venue: ACM SIGPLAN Notices (2008)

Language-based security relies on the assumption that all potential attacks are bound by the rules of the language in question. When programs are compiled into a different language, this is true only if the translation process preserves observational equivalence. We investigate the problem of fully abstract compilation, i.e., compilation that both preserves and reflects observational equivalence. In particular, we prove that typed closure conversion for the polymorphic »-calculus with existential and recursive types is fully abstract. Our proof uses operational techniques in the form of a step-indexed logical relation and construction of certain wrapper terms that "back-translate" from target values to source values. Although typed closure conversion has been assumed to be fully abstract, we are not aware of any previous result that actually proves this.
Group Statistics of DTI Fiber Bundles Using Spatial Functions of Tensor Measures
Authors: Casey B. Goodlett, P. Thomas Fletcher, John H. Gilmore, Guido Gerig
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We present a framework for hypothesis testing of differences between groups of DTI fiber tracts. An anatomical, tract-oriented coordinate system provides a basis for estimating the distribution of diffusion properties. The parametrization of sampled, smooth functions is normalized across a population using DTI atlas building. Functional data analysis, an extension of multivariate statistics to continuous functions is applied to the problem of hypothesis testing and discrimination. B-spline models of fractional anisotropy (FA) and Frobenius norm measures are analyzed jointly. Plots of the discrimination direction provide a clinical interpretation of the group differences. The methodology is tested on a pediatric study of subjects aged one and two years.
Development of Correct Graph Transformation Systems
Authors: Karl-Heinz Pennemann
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

A major goal of this thesis is the ability to determine the correctness of graphical specifications consisting of a graph precondition, a graph program and graph postcondition. According to Dijkstra, the correctness of program specifications can be shown by constructing a weakest precondition of the program relative to the postcondition and checking whether the precondition implies the weakest precondition. With the intention of tool support, we investigate the construction of weakest graph preconditions, consider fragments of graph conditions, for which the implication problem is decidable, and investigate an approximative solution of said problem in the general case. All research is done within the framework of adhesive high-level replacement categories. Therefore, the results will be applicable to different kinds of transformation systems and petri nets.
Towards a Multi-agent Model for Planning and Design of Exposition Spaces
Authors: Ivan Blecic, Arnaldo Cecchini, Giuseppe A. Trunfio, Jian Zhou, Wei Zang, Bing Liu
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

In this paper we present a multi-agent model for supporting the planning, design and organisation of exposition spaces. The model and its related software implementation simulates the behaviour of agents during their visit of an exposition with the objective to evaluate their overall comfort and satisfaction. It takes into account both the architectural and environmental aspects as well as the interaction among agents simulating possible phenomena of crowding and other forms of competition. The representation of the relevant phenomena in the model relies on the coexistence of both vector and cellular (raster) simulation approaches, taking into account the trade-off between the computational efficiency and the need for precision.