ppxscal/embedding_network huggingface dataset:
Dynaput: Dynamic Input Manipulations for 2D Structures of Mathematical Expressions
Authors: Deguchi Hiroaki
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This paper describes a prototype of input interface of GUI for mathematical expressions. Expressions are treated as sets of objects. To handle 2D structures, we have added new areas, called "peripheral area," to the objects. Based on new operations for these areas, the system provides dynamic interactive environment. The internal data structure for the interface is also presented in this paper. The tree structure of the objects is very simple, and has high potentiality for being converted to a variety of formats. Using this new dynamic input interface, users can manipulate 2D structures directly and intuitively, and they can get mathematical notations of wished format.
Improving Search Efficiency of Incremental Variable Selection by Using Second-Order Optimal Criterion
Authors: Kazumi Saito, Nobuaki Mutoh, Tetsuo Ikeda, Toshinao Goda, Kazuki Mochizuki
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

We address the problem of improving search efficiency of incremental variable selection. As one application, we focus on generalized linear models that are linear with respect to their parameters, but their objective functions are not restricted to a standard sum of squared error. In this paper, we present a method for incrementally selecting a set of relevant variables together with a newly proposing criterion based on second-order optimality for our models. In our experiments using a synthetic dataset with tens of thousands of variables, we show that the proposed method was able to completely restore the relevant variables. Moreover, the method substantially improved the search efficiency in comparison to a conventional calculation method. Furthermore, it is shown that we obtained promissing initial results using a real dataset in health-checkup.
Guided Sampling via Weak Motion Models and Outlier Sample Generation for Epipolar Geometry Estimation
Authors: Liran Goshen, Ilan Shimshoni
Venue: International Journal of Computer Vision (2008)

The problem of automatic robust estimation of the epipolar geometry in cases where the correspondences are contaminated with a high percentage of outliers is addressed. This situation often occurs when the images have undergone a significant deformation, either due to large rotation or wide baseline of the cameras. An accelerated algorithm for the identification of the false matches between the views is presented. The algorithm generates a set of weak motion models (WMMs). Each WMM roughly approximates the motion of correspondences from one image to the other. The algorithm represents the distribution of the median of the geometric distances of a correspondence to the WMMs as a mixture model of outlier correspondences and inlier correspondences. The algorithm generates a sample of outlier correspondences from the data. This sample is used to estimate the outlier rate and to estimate the outlier pdf. Using these two pdfs the probability that each correspondence is an inlier is estimated. These probabilities enable guided sampling. In the RANSAC process this guided sampling accelerates the search process. The resulting algorithm when tested on real images achieves a speedup of between one or two orders of magnitude.
Semantic impact graphs for information valuation
Authors: Sinan al-Saffar, Gregory L. Heileman
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

Information valuation has typically been carried out implicitly in question-answering and document retrieval systems. We argue that explicit information valuation is needed to move away from the system and process-centric nature of implicit valuation which has also hindered the theoretical study of information value under a unified and explicit framework. In this paper we present a graphical-based model for explicit information valuation. Our model caters to the subjective nature of information quality by measuring the impact a candidate piece of information may have on a knowledge base representing the recipient's world view. Our model is capable of evaluating information semantically at the statement level and is in effect basing information-valuation on information-understanding. However, information value can be computed and predicted using our causal graph model without requiring full logical inference typically needed for information-understanding.
A Survey of Modeling and Rendering Trees
Authors: Qi-Long Zhang, Ming-Yong Pang
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

As the representation of the vegetation, trees will be an indispensable part of natural scenes. Many studies have focused on the topic about how to simulate realistic trees efficiently. The goal of this paper is therefore to present an overview of methods applied to modeling and rendering of trees in complex natural scenes. These different types of representations and typical methods used in them are classified and analysized. Finally, we will conclude the paper with possible ideas and key points about modeling and rendering of trees for further research.
Motion and Appearance Nonparametric Joint Entropy for Video Segmentation
Authors: Sylvain Boltz, Ariane Herbulot, Eric Debreuve, Michel Barlaud, Gilles Aubert
Venue: International Journal of Computer Vision (2008)

This paper deals with video segmentation based on motion and spatial information. Classically, the motion term is based on a motion compensation error (MCE) between two consecutive frames. Defining a motion-based energy as the integral of a function of the MCE over the object domain implicitly results in making an assumption on the MCE distribution: Gaussian for the square function and, more generally, parametric distributions for functions used in robust estimation. However, these assumptions are not necessarily appropriate. Instead, we propose to define the energy as a function of (an estimation of) the MCE distribution. This function was chosen to be a continuous version of the Ahmad-Lin entropy approximation, the purpose being to be more robust to outliers inherently present in the MCE. Since a motion-only constraint can fail with homogeneous objects, the motion-based energy is enriched with spatial information using a joint entropy formulation. The resulting energy is minimized iteratively using active contours. This approach provides a general framework which consists in defining a statistical energy as a function of a multivariate distribution, independently of the features associated with the object of interest. The link between the energy and the features observed or computed on the video sequence is then made through a nonparametric, kernel-based distribution estimation. It allows for example to keep the same energy definition while using different features or different assumptions on the features.
Biodq: a model for data quality estimation and management in biological databases
Authors: Joachim Hammer
Venue:  (2007)

We present BIODQ, a model for estimating and managing the quality of biological data in genomics repositories. BIODQ uses our new Quality Estimation Model (QEM) which has been implemented as part of the Quality Management Architecture (QMA). The QEM consists of a set of quality dimensions and their quantitative measures. The QMA combines a series of software components that provide support for the integration of the QEM with existing biological repositories. We describe a research study conducted among biologists, which provides insights into the process of quality assessment in the biological context, and is the basis of our evaluation. The evaluation results show that the QEM dimensions and estimations are biologically-relevant and useful for discriminating high quality from low quality data. Additionally, the evaluation performed on a subset of the National Center for Biotechnology Information&rsquo;s databases validates the benefits of QMA as a quality-aware interface to genomics repositories. We expect BIODQ to benefit biologists and other users of genomics repositories by providing them with accurate information about the quality of the information that is returned as part of their queries.
Are polarizabilities useful as aromaticity indices? Tests on azines, azoles, oxazoles and thiazoles
Authors: Robert J. Doerksen, Valerie J. Steeves, Ajit J. Thakkar
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

Recent interest in quantitative aromaticity indices has focussed on structural, magnetic, and energetic criteria. In this work, aromaticity indices based on polarizabilities are compared with indices based upon bond orders for benzene and 12 azines, pyrrole and 9 azoles, furan and 9 oxazoles, and thiophene and 8 thiazoles. The best polarizability-based index of aromaticity we find is the polarizability anisotropy of the &pi;-electrons. However, none of the indices constructed from polarizabilities seem to be entirely suitable as measures of aromaticity. The comparison of the structural and polarizability scales enables us to formulate three critical tests that can be used to eliminate quickly unsuitable aromaticity scales for this set of heterocycles.
Detecting Current Outliers: Continuous Outlier Detection over Time-Series Data Streams
Authors: Kozue Ishida, Hiroyuki Kitagawa
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

The development of sensor devices and ubiquitous computing have increased time-series data streams. With data streams, current data arrives continuously and must be monitored. This paper presents outlier detection over data streams by continuous monitoring. Outlier detection is an important data mining issue and discovers outliers, which have features that differ profoundly from other objects or values. Most existing outlier detection techniques, however, deal with static data, which is computationally expensive. Specifically, for outlier detection over data streams, real-time response is very important. Existing techniques for static data, however, are fraught with many meaningless processes over data streams, and the calculation cost is too high. This paper introduces a technique that provides effective outlier detection over data streams using differential processing, and confirms effectiveness.
The PCR Primer Design as a Metaheuristic Search Process
Authors: L. Montera, M. C. Nicoletti
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

The Polymerase Chain Reaction process is a well-known technique for the in vitro amplification of a DNA sequence. The success of a PCR depends on several parameters particularly the primer sequences used. Since the design of a suitable pair of primer involves a reasonable number of variables, which can have a range of different values, computer programs are commonly used to assist this task. This paper approaches the design of a pair of primer sequences as a search process throughout the space defined by all possible primer sequence pairs, directed by an evaluation function that combines the many variables involved in a primer design; an experiment and its results are discussed.
Fault-Tolerant Memory Design and Partitioning Issues in Embryonics
Authors: Lucian Prodan, Mihai Udrescu, Mircea Vladutiu
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

In the quest of designing extremely fault-tolerant computing systems drawing inspiration from nature is one avenue worth exploring. Embryonics (embryonic electronics) is a research project that attempts to implement features otherwise available in the world of biology to design robust, massively parallel arrays of processors. This paper elaborates on some of the design approaches undertaken in order to ensure a high level of fault-tolerance as well as on how to partition the array in order to optimally make use of spare resources.
Test Construction for Mathematical Functions
Authors: Victor Kuliamin
Venue: Proceedings of the 20th IFIP TC 6/WG 6.1 international conference on Testing of Software and Communicating Systems: 8th International Workshop (2008)

The article deals with problems of testing implementations of mathematical functions working with floating-point numbers. It considers current standards' requirements to such implementations and demonstrates that those requirements are not sufficient for correct operation of modern systems using sophisticated mathematical modeling. Correct rounding requirement is suggested to guarantee preservation of all important properties of implemented functions and to support high level of interoperability between different mathematical libraries and modeling software using them. Test construction method is proposed for conformance test development for current standards supplemented with correct rounding requirement. The idea of the method is to use three different sources of test data: floating-point numbers satisfying specific patterns, boundaries of intervals of uniform function behavior, and points where correct rounding requires much higher precision than in average. Some practical results obtained by using the method proposed are also presented.
Social Mediation for Collective Intelligence in a Large Multi-agent Communities: A Case Study of AnnotGrid
Authors: Jason J. Jung, Geun-Sik Jo
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Collective intelligence is a key issue for efficient collaborations on semantic grid environment. Through interactions among agents on the semantic grid, we want to discover social centralities underlying on agent communities. In this paper, we propose an ontology mapping approach to build collective intelligence based on social mediation. As a case study, we demonstrate AnnotGrid platform to support manual annotation tasks of image dataset.
Deterministic Input-Reversal and Input-Revolving Finite Automata
Authors: Suna Bensch, Henning Bordihn, Markus Holzer, Martin Kutrib
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

Extended finite automata are finite state machines with the additional ability to manipulate the remaining part of the input. We investigate three types of deterministic extended automata, namely left-revolving, right-revolving, and input reversal finite automata. Concerning their computational capacity it is shown that nondeterminism is better than determinism, that is, for all three types of automata there is a language accepted by the nondeterministic versions but not accepted by any deterministic automaton of the same type. Concerning the closure properties most of the language families studied are not closed under standard operations. In particular, we show that the family of languages accepted by deterministic right-revolving finite automata is an anti-AFL which is not closed under reversal and intersection.
Coverage preserved scheduling in a heterogeneous sensor network
Authors: Kendall E. Nygard
Venue:  (2007)

From the battlefield to everyday life, health, safety, education, exploration, surveillance, the operation table, and construction, everywhere sensors and a sensor network are being used. Due to the heavy increase in the use of sensor networks, it is a very significant research field. There is no complete bundle of solutions for a sustainable sensor network. In this research, we design the differentiated, coverage-preserved, sensor-scheduling model of a heterogeneous sensor network. We implement an optimization solver which minimizes the cost of a generalized network flow model. The development phase of the code also took a significant software engineering research effort. Our code gives the similar optimal value like commercial codes. In the next phase, we design the network flow model of a sensor network. We generate test cases by writing code and do the empirical testing. We show the optimal value which is the minimum number of duty cycles to provide the coverage of a feasible network. Our algorithm can check the feasibility of the problem domain. Our method also computes the saved duty cycles if the minimum numbers of sensors are awake. In fact, this research introduces a novel method to find optimal scheduling in a heterogeneous sensor network. In our model, we simulate sensor scheduling using different inputs, such as battery life-time which is represented by different numbers of duty cycles, different numbers of sensor nodes, and different sizes of network area which are represented by the sets of grid-points. We simulate with different coverage capabilities of sensors and with different levels of coverage requirements at the grid-points. We implement another heuristic which keeps a sensor "on" based on its maximum coverage capability to compare the coverage performance of our method. We show that our method performs better. We show that the heuristic does not meet the demand of a sensor network. Our scheduling method spends the minimum number of duty cycles providing coverage.
Stock Company Comprehensive Assessment Model Based on Kohonen Network
Authors: Xuming Han, Limin Wang
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

Research on stock company comprehensive assessment has always been an important focus for economists and computer experts. In this paper, the financial indexes reflecting the comprehensive capability of stock companies as main research objects including income per thigh, clean asset per thigh, profit rate of clean asset, Kohonen network with the advantage of clustering is applied to assess for stock companies. In order to improve the precision of solutions, a tabu-mapping method is also used to avoid the same output node to be mapped by more than one input in this paper. Experimental results show that Kohonen network is feasible and effective to assess stock companies, it could provide a new reference basis for government and investors, which has potential applications in the financial field.
Abstract Modeling and Formal Verification of Microprocessors
Authors: Ziyad Hanna
Venue: Proceedings of the 2nd international symposium on Computer Science in Russia: Theory and Applications (2007)

Moore's Law continues to drive a severe increase in the number of transistors that can be integrated onto a single microprocessor chip. Computer architects and designers continue to look for ways to take advantage from it to produce ever more complex microprocessors. Meanwhile, market forces are dictating a shorter time to market, a proliferation of product and steeper volume ramps in production. However, it is evident that logic correctness is one of the main challenges that computer engineers usually face during the design and validation of such systems.In the last 20 years, researchers and industrial experts invented several modeling and validation technologies, such as logic simulation, fast hardware emulation engines, and formal methods. However the design size and complexity continue to grow and outstrip what the validation techniques can do for producing high quality and correct systems. As a results, the validation problem is becoming more complex to solve and is indeed the main limiter for producing a high quality silicon products.Design abstraction and high level modeling is a fundamental design strategy to cope with system complexity. The basic idea is to hide design implementation details, while focusing on design specification, capturing the pure logic properties and behaviors of the system. Doing this, we believe that the size of the design model can be dramatically decreased because none functional or physical properties of the design are excluded. Therefore the design representation is purely logical and have a clear semantics which it becomes easier to understand, easier and faster to validate using dynamic or formal techniques, so design errors can be detected earlier before going into detailed implementation and thus avoid a costly design iterations due to late soundness issues.In this talk we will present abstract modeling techniques and their verification challenges. In particular we will describe the Abstract State Machines approach for modeling and verification of high level models. In addition we will outline several research topics in this domain to encourage the academic community to take an active part in exploring and developing new verification methods that can cope with the increasing complexity of microprocessors' design.
Heterogeneous Design in Functional DIF
Authors: William Plishker, Nimish Sane, Mary Kiemb, Shuvra S. Bhattacharyya
Venue: Proceedings of the 8th international workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2008)

Dataflow formalisms have provided designers of digital signal processing systems with analysis and optimizations for many years. As system complexity increases, designers are relying on more types of dataflow models to describe applications while retaining these implementation benefits. The semantic range of DSP-oriented dataflow models has expanded to cover heterogeneous models and dynamic applications, but efficient design, simulation, and scheduling of such applications has not. To facilitate implementing heterogeneous applications, we utilize a new dataflow model of computation and show how actors designed in other dataflow models are directly supported by this framework, allowing system designers to immediately compose and simulate actors from different models. Using an example, we show how this approach can be applied to quickly describe and functionally simulate a heterogeneous dataflow-based application such that a designer may analyze and tune trade-offs among different models and schedules for simulation time, memory consumption, and schedule size.
Using Arithmetic Coding for Reduction of Resulting Simulation Data Size on Massively Parallel GPGPUs
Authors: Ana Balevic, Lars Rockstroh, Marek Wroblewski, Sven Simon
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

The popularity of parallel platforms, such as general purpose graphics processing units (GPGPUs) for large-scale simulations is rapidly increasing, however the I/O bandwidth and storage capacity of these massively-parallel cards remain the major bottle necks. We propose a novel approach for post-processing of simulation data directly on GPGPUs by efficient data size reduction immediately after simulation that can considerably reduce the influence of these bottlenecks on the overall simulation performance, and present current performance results.
Machine intelligence (MI), competence and creativity
Authors: Rajakishore Nath
Venue: AI Society (2008)

In mid-twentieth century, the hypothesis, &#x2018;a machine can think&#x2019; became very popular after, Alan Turing&#x2019;s article on &#x2018;Computing Machinery and Intelligence&#x2019;. This hypothesis, &#x2018;a machine can think&#x2019; established the foundations of machine intelligence (MI), and claimed that machines have consciousness and creativity, with the power to compete with human beings. In the first section, I shall show how consciousness and creativity is conceptualized in the domain of MI. The main aim of MI is not only to construct difficult programs to solve our day-to-day problems, but also to reproduce mentality in machines. It was claimed that all the mental qualities are ascribable to machines. My intention in this paper is to clarify consciousness and creativity from a subjective point of view. My claim is that consciousness and creativity cannot be fully represented in a mechanistic domain. There are subjective mental or conscious states, which can be seen in a first-person perspective of their proper understanding.