ppxscal/embedding_network huggingface dataset:
Circuits and algorithms for pipelined adcs in scaled cmos technologies
Authors: Hae-Seung Lee, Gregory Wornell
Venue:  (2008)

CMOS technology scaling is creating significant issues for analog circuit design. For example, reduced signal swing and device gain make it increasingly difficult to realize high-speed, high-gain feedback loops traditionally used in switched capacitor circuits. This research involves two complementary methods for addressing scaling issues. First is the development of two blind digital calibration techniques. Decision Boundary Gap Estimation (DBGE) removes static non-linearities and Chopper Offset Estimation (COE) nulls offsets in pipelined ADCs. Second is the development of circuits for a new architecture called zero-crossing based circuits (ZCBC) that is more amenable to scaling trends. To demonstrate these circuits and algorithms, two different ADCs were designed: an 8 bit, 200MS/s in TSMC 180nm technology, and a 12 bit, 50 MS/s in IBM 90nm technology. Together these techniques can be enabling technologies for both pipelined ADCs and general mixed signal design in deep sub-micron technologies. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Toward automatic generation of image-text document surrogates to optimize cognition
Authors: Eunyee Koh, Andruid Kerne, Jon Moeller
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

The representation of information collections needs to be optimized for human cognition. Growing information collections play a crucial role in human experiences. While documents often include rich visual components, collections, including personal collections and those generated by search engines, are typically represented lists of text-only surrogates. By concurrently invoking complementary components of human cognition, combined image-text surrogates help people to more effectively see, understand, think about, and remember information collection. This research develops algorithmic methods that use the structural context of images in HTML documents to associate meaningful text and thus derive combined image-text surrogates.
Pseudo-dynamics model of a cantilever beam for animating flexible leaves and branches in wind field
Authors: Shaojun Hu, Tadahiro Fujimoto, Norishige Chiba
Venue: Computer Animation and Virtual Worlds (2009)

We present a pseudo-dynamics model of a cantilever beam to visually simulate motions of leaves and branches in a wind field by considering the influence of natural frequency (f0) and damping ratio (e). Our pseudo-dynamics model consists of a static equilibrium model, which can handle the bending of a curved beam loaded by an arbitrary force in three-dimensions, and a dynamic motion model that describes the dynamic response of the beam subjected to turbulence. Using the static equilibrium model, we can apply it to controlling the free bending of petioles and branches. Furthermore, we extend it to a surface deformation model that can deform some flexible laminae. Based on a mass spring system, we analyze the property of dynamic response of a cantilever beam in turbulence with various combinations of f0 and e, and we give some guidelines to determine the combination types of branches and leaves according to their shapes and stiffness. The main advantage of our techniques is that we are able to deform curved branches and some flexible leaves dynamically by taking account of their structures. Finally, we demonstrate that our proposed method is effective by showing various motions of leaves and branches with different model parameters. Copyright &copy; 2009 John Wiley & Sons, Ltd. We present a static equilibrium model of a curved cantilever beam to bend branches or petioles, and we extend it to deform flexible laminae. Combined with a mass spring system-based dynamic model, we generate a pseudo-dynamics model and analyze the combination cases of natural frequency and damping ratio. Finally, we give some guidelines to determine the combination types of branches and leaves according to their structures and implement their motion in wind fields with different model parameters.
On Parameterized Exponential Time Complexity
Authors: Jianer Chen, Iyad A. Kanj, Ge Xia
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

In this paper, we show that special instances of parameterized NP-hard problems are as difficult as the general instances in terms of their subexponential time computability. For example, we show that the Planar Dominating Set problem on degree-3 graphs can be solved in $2^{o(\sqrt{k})} p(n)$ parameterized time if and only if the general Planar Dominating Set problem can. Apart from their complexity theoretic implications, our results have some interesting algorithmic implications as well.
Size does matter: two certified abstractions to disprove entailment in intuitionistic and classical separation logic
Authors: Clément Hurlin, François Bobot, Alexander J. Summers
Venue: International Workshop on Aliasing, Confinement and Ownership in Object-Oriented Programming (2009)

We describe an algorithm to disprove entailment between separation logic formulas. We abstract models of formulas by their size and check whether two formulas have models whose sizes are compatible. Given two formulas A and B that do not have compatible models, we can conclude that A &nvdash; B. We provide two different abstractions (of different precision) of models. Our algorithm is of interest wherever entailment checking is performed (such as in program verifiers)
Technical Section: Computing smooth approximations of scalar functions with constraints
Authors: Giuseppe Patanè, Bianca Falcidieno
Venue: Computers and Graphics (2009)

In engineering, geographical applications, scientific visualization, and bio-informatics, a variety of phenomena is described by a large set of data modeled as the values of a scalar function f:M->R defined on a surface M. A low quality of the discrete representations of the input data, unstable computations, numerical approximations, and noise might produce functions with a high number of critical points. In this context, we propose an algorithmic framework for smoothing an arbitrary scalar function, while simplifying its redundant critical points and preserving those that are mandatory for its description. From our perspective, the critical points of f are a natural choice to guide the approximation scheme; in fact, they usually represent relevant information about the behavior of f or the shape itself. To address the aforementioned aims, we compute a smooth approximation f@?:M->R of f whose set of critical points contains those that have been preserved by the simplification process. The idea behind the proposed approach is to combine smoothing techniques, critical points, and spectral properties of the Laplacian matrix. Inserting constraints in the smoothing of f allows us to overcome the traditional error-driven approximation of f, which does not provide constraints on the preserved topological features. Finally, the computational cost of the proposed approach is O(nlogn), where n is the number of vertices of M.
Difficulty of linkage learning in estimation of distribution algorithms
Authors: Si-Cheng Chen, Tian-Li Yu
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

This paper investigates the difficulty of linkage learning, an essential core, in EDAs. Specifically, it examines allelicpairwise independent functions including the parity, paritywith-trap, and Walsh-code functions. While the parity function was believed to be difficult for EDAs in previous work, our experiments indicate that it can be solved by CGA within a polynomial number of function evaluations to the problem size. Consequently, the apparently difficult paritywith-trap function can be easily solved by ECGA, even though the linkage model is incorrect. A convergence model for CGA on the parity function is also derived to verify and support the empirical findings. Finally, this paper proposes a socalled Walsh-code function, which is more difficult than the parity function. Although the proposed function does deceive the linkage-learning mechanism in most EDAs, EDAs are still able to solve it to some extent.
Network science: an introduction to recent statistical approaches
Authors: Stanley Wasserman
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Network science focuses on relationships between social entities. It is used widely in the social and behavioral sciences, as well as in political science, economics, organizational science, and industrial engineering. The social network perspective has been developed over the last sixty years by researchers in psychology, sociology, and anthropology, and morerecently, to a lesser extent, in physics. Network science is gaining recognition and standing in the general social and behavioral science communities as the theoretical basis for examining social structures. This basis has been clearly defined by many theorists, and the paradigm convincingly applied to important substantive problems. However, the paradigm requires a new and different set of concepts and analytic tools, beyond those provided by standard quantitative (particularly, statistical) methods. These concepts and tools are the topics of this talk.
The Decision-Making Journey of a Family Carer: Information and Social Needs in a Cultural Context
Authors: Lemai Nguyen, Graeme Shanks, Frank Vetere, Steve Howard
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

While the important role of family as carer has been increasingly recognised in healthcare service provision, particularly for patients with acute or chronic illnesses, the carer's information and social needs have not been well understood and adequately supported. In order to provide continuous and home-based care for the patient, and to make informed decisions about the care, a family carer needs sufficient access to medical information in general, the patient's health information specifically, and supportive care services. Two key challenges are the carer's lack of medical knowledge and the many carers with non-English speaking and different cultural backgrounds. The informational and social needs of family carers are not yet well understood. This paper analyses the web-log of a husband-carer who provided support for his wife, who at the time of care was a lung cancer patient. It examines the decision-making journey of the carer and identifies the key issues faced in terms of informational and social practices surrounding care provision.
The Kleene Language for Weighted Finite-State Programming
Authors: Kenneth R. Beesley
Venue: Proceeding of the 2009 conference on Finite-State Methods and Natural Language Processing: Post-proceedings of the 7th International Workshop FSMNLP 2008 (2009)

Kleene is a high-level programming language for building, manipulating and testing weighted finite-state acceptors and transducers. It allows users to define networks using regular expressions and right-linear phrase-structure grammars, and it provides variables, functions and familiar control structures. Pre-edited Kleene scripts can be run from the command line, and a graphical user interface is provided for interactive programming and testing. The Kleene parser is implemented in JavaCC/JJTree, and the interpreter calls functions in the OpenFst library via the Java Native Interface (JNI). The design, implementation, development status and future plans for Kleene are described.
Selecting Regions of Interest for the Diagnosis of Alzheimer Using Brain SPECT Images
Authors: Diego Salas-Gonzalez, Juan M. Górriz, Javier Ramírez, Ignacio Álvarez, Míriam López, Fermín Segovia, Carlos G. Puntonet
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

This paper presents a computer-aided diagnosis technique for improving the accuracy of the early diagnosis of the Alzheimer type dementia. The proposed methodology is based on the selection of those voxels which present a greater difference between normals and Alzheimer's type dementia patients. The mean value of the intensities of the selected voxels are used as features for different classifiers. The proposed methodology reaches an accuracy of 89% in the classification task.
Simple iterative algorithm for image enhancement
Authors: Barbara Barišic, Mirjana Bonkovic, Spomenka Bovan
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

Image enhancement methods can be divided in two groups: the ones that use only one single image and the ones that rely on specific training set or use multiple images. In this paper it is introduced an iterative algorithm based on the quasi-Newton methods, with the objective to enhance resolution only by one single image. In the paper there will be compared results gained depending on the objective histogram: spline histogram and one augmented with Empirical Mode Decomposition.
Classifying genes according to predefined patterns by controlling false discovery rate
Authors: Hae-Sang Park, Chi-Hyuck Jun, Joo-Yeon Yoo
Venue: Expert Systems with Applications: An International Journal (2009)

Classifying genes with time-course expression data into one of the several predefined patterns is viewed as a multiple significance testing problem. The proposed approach calculates the p-value of test statistic using the Monte Carlo method and classifies genes by controlling the overall false discovery rate. We also estimate the positive false discovery rate of each pattern. The proposed procedure was applied to a real data set and some numerical experiments using synthetic data are performed.
Optimizing a Pseudo Financial Factor Model with Support Vector Machines and Genetic Programming
Authors: Matthew Butler, Vlado Kešelj
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

We compare the effectiveness of Support Vector Machines (SVM) and Tree-based Genetic Programming (GP) to make accurate predictions on the movement of the Dow Jones Industrial Average (DJIA). The approach is facilitated though a novel representation of the data as a pseudo financial factor model, based on a linear factor model for representing correlations between the returns in different assets. To demonstrate the effectiveness of the data representation the results are compared to models developed using only the monthly returns of the inputs. Principal Component Analysis (PCA) is initially used to translate the data into PC space to remove excess noise that is inherent in financial data. The results show that the algorithms were able to achieve superior investment returns and higher classification accuracy with the aid of the pseudo financial factor model. As well, both models outperformed the market benchmark, but ultimately the SVM methodology was superior in terms of accuracy and investment returns.
Interactive shadowing for 2D Anime
Authors: Eiji Sugisaki, Hock Soon Seah, Feng Tian, Shigeo Morishima
Venue: Computer Animation and Virtual Worlds (2009)

In this paper, we propose an instant shadow generation technique for 2D animation, especially Japanese Anime. In traditional 2D Anime production, the entire animation including shadows is drawn by hand so that it takes long time to complete. Shadows play an important role in the creation of symbolic visual effects. However shadows are not always drawn due to time constraints and lack of animators especially when the production schedule is tight. To solve this problem, we develop an easy shadowing approach that enables animators to easily create a layer of shadow and its animation based on the character's shapes. Our approach is both instant and intuitive. The only inputs required are character or object shapes in input animation sequence with alpha value generally used in the Anime production pipeline. First, shadows are automatically rendered on a virtual plane by using a Shadow Map1 based on these inputs. Then the rendered shadows can be edited by simple operations and simplified by the Gaussian Filter. Several special effects such as blurring can be applied to the rendered shadow at the same time. Compared to existing approaches, ours is more efficient and effective to handle automatic shadowing in real-time. Copyright &copy; 2009 John Wiley & Sons, Ltd. Our shadowing approach is easy and intuitive, and renders shadows automatically by setting character's image sequence with alpha value as input. After rendering the shadows, animators can edit the rendered shadows for casting direction and shape globally, and then edit shadows locally by applying Gaussian Filter to blur the rendered shadows.
Standard-Compliant Scenario Building with Theoretical Justification in a Theory-Aware Authoring Tool
Authors: Yusuke Hayashi, Jacqueline Bourdeau, Riichiro Mizoguchi
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Nowadays standard technologies play important roles in enhancing sharability, reusability and interoperability of learning contents. However, there is a lack of pedagogical justification of the contents implemented with the standards. This paper discusses the standard-compliance of our ontology-based modeling framework and how the framework gives theoretical justification to standard-compliant learning/instructional scenarios in a theory-aware authoring tool.
Establishment of machining functions in the electro-erosion manufacture of interior threads from sintered metallic carbides
Authors: Corneliu Neagu, Andrei Dumitrescu, Mihaela Berinde
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

The emergence of new materials and alloys, especially the hard and extrahard ones, has leaded to the necessity of industrial use of non-conventional machining procedures. Amongst them, the electro-erosion has an important share, due to its technological advantages. In this paper, the authors present some of the results obtained in their theoretical and experimental researches regarding the machining of interior threads in sintered metallic carbide using copper electrode. These results are mainly about the influence of electro-technological parameters on thread's pitch p and flank angle α. The focus of researches is the establishment of machining functions that will be useful in the determination of electro-technological parameters for electro-erosion of interior threads from sintered metallic carbides G20.
A generalized cohesive element technique for arbitrary crack motion
Authors: Spandan Maiti, Dipankar Ghosh, Ghatu Subhash
Venue: Finite Elements in Analysis and Design (2009)

A computational method for arbitrary crack motion through a finite element mesh, termed as the generalized cohesive element technique, is presented. In this method, an element with an internal discontinuity is replaced by two superimposed elements with a combination of original and imaginary nodes. Conventional cohesive zone modeling, limited to crack propagation along the edges of the elements, is extended to incorporate the intra-element mixed-mode crack propagation. Proposed numerical technique has been shown to be quite accurate, robust and mesh insensitive provided the cohesive zone ahead of the crack tip is resolved adequately. A series of numerical examples is presented to demonstrate the validity and applicability of the proposed method.
Guest Editor's Introduction: Examples of Management Decision Criteria
Authors: Yervant Zorian
Venue: IEEE Design Test (2009)

Consumer application chips are the technology drivers today. Their design and test require different types of optimizations to address, on the one hand, the technology challenges, and on the other, very high volume production. This will necessitate adopting emerging solutions to meet such requirements. Optimizing for high-volume production, low power, and shrinking sizes necessitates adequate trade-off analysis, along with technical and business decision making by management. Also, moving to new semiconductor technology nodes, such as 45 nm and 32 nm, can significantly affect the choices of suppliers. This special issue discusses these requirements and demonstrates corresponding management decision criteria to make the right choices from a pool of alternate options for flows, methodologies, tools, and IP blocks. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
FpViz: a visualizer for frequent pattern mining
Authors: Carson Kai-Sang Leung, Christopher L. Carmichael
Venue: Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration (2009)

Over the past 15 years, numerous algorithms have been proposed for frequent pattern mining as it plays an essential role in many knowledge discovery and data mining (KDD) tasks. Most of these frequent pattern mining algorithms return the mined results in the form of textual lists containing frequent patterns showing those frequently occurring sets of items. It is well known that "a picture is worth a thousand words". The use of visual representation can enhance the user understanding of the inherent relations in a collection of frequent patterns. A few visualizers have been developed to visualize the input data or the mined results. However, most of these visualizers were not designed for visualizing the mined frequent patterns. In this paper, we develop a visualizer for frequent pattern mining. Such a visualizer---called FpViz---gives users an insight about the data, allows them to zoom in and zoom out, and provides details on demand. Moreover, FpViz is also equipped with several interactive features for effective visual support in the data analysis and KDD process for various real-life applications.
Constrained Shortest Paths and Related Problems - Constrained Network Optimization
Authors: Mark Ziegelmann
Venue:  (2007)

The shortest path problem arises in various applied settings where some material (e.g., computer data packet, telephone calls, vehicles) is sent between two specified points in a network as quickly, cheaply or reliably as possible. In practice we want to optimize a combination of those criteria (i.e., we have a bi- or multicriteria shortest path problem). This book proposes a 2-step method for the constrained shortest path problem. A relaxation is solved to get upper and lower bounds and then the gap is closed with clever path ranking to obtain the exact solution. Different old and new methods are compared both theoretically and experimentally. The proposed 2-step method also works for a more general class of constrained network optimization problems. In addition the generic approach is illustrated with several examples and a newly developed Constrained Network Optimization Software Package (CNOP) is introduced that provides this generic 2-step approach as well as all state of the art algorithms for constrained shortest paths. This book is a valuable resource for researchers, students as well as practitioners working on the constrained shortest path problem and related problems. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player