ppxscal/embedding_network huggingface dataset:
The Image Foresting Transform: Theory, Algorithms, and Applications
Authors: Alexandre X. Falcão, Jorge Stolfi, Roberto de Alencar Lotufo
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

Abstract--The image foresting transform (IFT) is a graph-based approach to the design of image processing operators based on connectivity. It naturally leads to correct and efficient implementations and to a better understanding of how different operators relate to each other. We give here a precise definition of the IFT, and a procedure to compute it--a generalization of Dijkstra's algorithm--with a proof of correctness. We also discuss implementation issues and illustrate the use of the IFT in a few applications.
Migrating Web Frameworks Using Water Transformations
Authors: Ahmed E. Hassan, Richard C. Holt
Venue: Proceedings of the 27th Annual International Conference on Computer Software and Applications (2003)

We propose an approach (based on Water Transformations)to migrate web applications between various web developmentframeworks. This migration process preserves thestructure of the code and the location of comments to easefuture manual maintenance of the migrated code. Developerscan move their applications to the framework that meetstheir current needs instead of being locked into their initialdevelopment framework. We give an example of using ourapproach to migrate a web application written using ActiveServer Pages (ASP) framework to Netscape Server Pages(NSP) framework.
Automatical detection of face features and exact face contour
Authors: Vytautas Perlibakas
Venue: Pattern Recognition Letters (2003)

The approach based on the mathematical morphology and the variational calculus is presented for the detection of an exact face contour in still grayscale images. The facial features (eyes and lips) are detected by using the mathematical morphology and the heuristic rules. Using these features an image is filtered and an edge map is prepared. The face contour is detected by minimizing its internal and external energy. The internal energy is defined by the contour tension and the rigidity. The external energy is defined by using the generalized gradient vector flow field of the image edge map. Initial contour is calculated using the detected face features. The contour detection experiments were performed using the database of 427 face images. Automatically detected contours were compared with manually labeled contours using an area and the Euclidean distance-based error measures.
Dimensionality Reduction Using Kernel Pooled Local Discriminant Information
Authors: Peng Zhang, Jing Peng, Carlotta Domeniconi
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

We study the use of kernel subspace methods for learninglow-dimensional representations for classification. We proposea kernel pooled local discriminant subspace methodand compare it against several competing techniques: generalizedFisher discriminant analysis (GDA) and kernelprincipal components analysis (KPCA) in classificationproblems. We evaluate the classification performance ofthe nearest-neighbor rule with each subspace representation.The experimental results demonstrate the efficacy ofthe kernel pooled local subspace method and the potentialfor substantial improvements over competing methods suchas KPCA in some classification problems.
A corpus-based evaluation of centering and pronoun resolution
Authors: Joel R. Tetreault
Venue: Computational Linguistics (2001)

In this paper we compare pronoun resolution algorithms and introduce a centering algorithm (Left-Right Centering) that adheres to the constraints and rules of centering theory and is an alternative to Brennan, Friedman, and Pollard's (1987) algorithm. We then use the Left-Right Centering algorithm to see if two psycholinguistic claims on Cf-list ranking will actually improve pronoun resolution accuracy. Our results from this investigation lead to the development of a new syntax-based ranking of the Cf-list and corpus-based evidence that contradicts the psycholinguistic claims.
Object-level structured contour map extraction
Authors: R. Bergevin, A. Bubel
Venue: Computer Vision and Image Understanding (2003)

A new approach is proposed to extract an object-level structured contour map from the junctions in a 2D image. Local junction structures are paired in order to initialize and globally constrain the contour extraction process. An original optimization method is applied to detect and describe the contours in respect of their inherent shape and structure. Any given contour is described using a proper number of constant-curvature primitives according to the complexity of its shape. The contour map produced is represented as a graph. The characterized contours correspond to the edges of the graph and their topological structure is described by the junctions at the vertices. An elaborated experimental evaluation illustrates the capabilities of the proposed approach in demanding situations.
An Architectural Framework for Native XML Data Management
Authors: Khin-Myo Win, Wee-Keong Ng, Ee-Peng Lim
Venue: Proceedings of the 2003 International Conference on Cyberworlds (2003)

With rapid increase of semistructured data over the Web,XML becomes popular to represent such data and emergesas a de facto standard for information exchange amonge-business applications. Since XML data are widely distributed,new native XML database systems, which arespecifically tailored for managing such data, become necessary.Unlike data in conventional databases, XML hasspecial characteristics and constraints, thus, well-definedarchitectural framework for conventional databases are notcompletely relevant to be adopted in native databases. Currentstate-of-the-art native databases employed their ownarchitectures in their database designs, as a result, they areinconsistent and there is still lack of a common architecturalframework that can be referenced by future XML databasedesigners. We aim to fulfill this requirement. In this paper,we propose a general and an extended architectural frame-worksthat are derived from our practical experience ondesigning an efficient storage for XML data while preservingdesirable features and possible constraints. The validationdemonstrates that the proposed framework coversthe architectures employed in current state-of-the-art nativedatabase systems.
Voltage-Clock-Scaling Adaptive Scheduling Techniques for Low Power in Hard Real-Time Systems
Authors: C. M. Krishna, Yann-Hang Lee
Venue: IEEE Transactions on Computers (2003)

Abstract--Many embedded systems operate under severe power and energy constraints. Voltage clock scaling is one mechanism by which energy consumption may be reduced: It is based on the fact that power consumption is a quadratic function of the voltage, while the speed is a linear function. In this paper, we show how voltage scaling can be scheduled to reduce energy usage while still meeting real-time deadlines.
Generating Discriminating Cartoon Faces Using Interacting Snakes
Authors: Rein-Lien Hsu, Anil K. Jain
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

As a computational bridge between the high-level a priori knowledge of object shape and the low-level image data, active contours (or snakes) are useful models for the extraction of deformable objects. We propose an approach for manipulating multiple snakes iteratively, called interacting snakes, that minimizes the attraction energy functionals on both contours and enclosed regions of individual snakes and the repulsion energy functionals among multiple snakes that interact with each other. We implement the interacting snakes through explicit curve (parametric active contours) representation in the domain of face recognition. We represent human faces semantically via facial components such as eyes, mouth, face outline, and the hair outline. Each facial component is encoded by a closed (or open) snake that is drawn from a 3D generic face model. A collection of semantic facial components form a hypergraph, called semantic face graph, which employs interacting snakes to align the general facial topology onto the sensed face images. Experimental results show that a successful interaction among multiple snakes associated with facial components makes the semantic face graph a useful model for face representation, including cartoon faces and caricatures, and recognition.
Building signature-trees on path signatures in document databases
Authors: Yangjun Chen, Gerald Huck
Venue: Effective databases for text & document management (2003)

Java is a prevailing implementation platform for XML-based systems. Several high-quality in-memory implementations for the standardized XML-DOM API are available. However, persistency support has not been addressed. In this chapter, we discuss this problem and introduce PDOM (persistent DOM) to accommodate documents as permanent object sets. In addition, we propose a new indexing technique: path signatures to speed up the evaluation of path-oriented queries against document object sets, which is further enhanced by combining the technique of signature-trees with it to expedite scanning of signatures stored in a physical file.
Realizations of coupled vectors in the tensor product of representations of su(1, 1) and su(2)
Authors: S. Lievens, J. Van der Jeugt
Venue: Journal of Computational and Applied Mathematics (2003)

Using the realization of positive discrete series representations of su(1,1) in terms of a complex variable z, we give an explicit expression for coupled basis vectors in the tensor product of v + 1 representations as polynomials in v + 1 variables z1,.....,zv+1. These expressions use the terminology of binary coupling trees (describing the coupled basis vectors), and are explicit in the sense that there is no reference to the Clebsch-Gordan coefficients of su(1,1). In general, these polynomials can be written as (terminating) multiple hypergeometric series. For v=2, these polynomials are triple hypergeometric series, and a relation between the two binary coupling trees yields a relation between two triple hypergeometric series. The cast of su(2) is discussed next. Also here the polynomials are determined explicitly in terms of a known realization; they yield an efficient way of computing coupled basis vectors in terms of uncoupled basis vectors.
A coarse-grain parallel genetic algorithm for finding Ramsey Numbers
Authors: Iker Gondra, Mansur H. Samadzadeh
Venue: Proceedings of the 2003 ACM symposium on Applied computing (2003)

Ramsey Theory studies the existence of highly regular patterns within a large system or a set of randomly selected points or numbers. The role of Ramsey Numbers is to quantify some of the general existential theorems in Ramsey Theory. Attempting to find Ramsey Numbers has been an arduous task that is too often unfruitful. Only a handful of specific numbers are known. Genetic Algorithms (GA), which are based on the idea of optimizing by simulating the natural processes of evolution, have proven successful in solving complex problems that are not easily solved through conventional methods. However, premature convergence is an inherent characteristic of traditional GAs that makes them incapable of searching numerous points in a problem domain. Parallel GA (PGA) is an extension of the classical GA that takes advantage of a GA's inherent parallelism to improve its time performance and reduce the likelihood of premature convergence. A cgGA (Coarse-Grain GA) maintains a number of independent populations and allows for the occasional interchange of individuals. In this manner, a cgGA increases the diversity of search paths and helps to stop premature convergence to nonoptimal solutions. Given this motivation, a tool was developed, called SIPAGAR (Simulated Parallel Genetic Algorithm for finding Ramsey Numbers), that allows us to verify and validate the superior performance of cgGAs over traditional GAs applied to the problem of improving the bounds of classical Ramsey Numbers. Significant differences between the simulated cgGA and traditional GA were observed in both the premature convergence rate and the quality of the results. This leads us to the conclusion that future cgGA-based attempts to improve the bounds of Ramsey Numbers will probably be more promising than those based on traditional GAs.
Structure preservation: a challenge in computational control
Authors: Peter Benner, Daniel Kressner, Volker Mehrmann
Venue: Future Generation Computer Systems (2003)

Current and future directions in the development of numerical methods and numerical software for control problems are discussed. Major challenges include the demand for higher accuracy, robustness of the method with respect to uncertainties in the data or the model, and the need for methods to solve large scale problems. To address these demands it is essential to preserve any underlying physical structure of the problem. At the same time, to obtain the required accuracy it is necessary to avoid all inversions or unnecessary matrix products. We will demonstrate how these demands can be met to a great extent for some important tasks in control, the linear-quadratic optimal control problem for first and second order systems as well as stability radius and H∞ norm computations.
An experience on students' participation in blended vs. online styles of learning
Authors: Juan Manuel Dodero, Camino Fernández, Daniel Sanz
Venue: ACM SIGCSE Bulletin (2003)

This work compares two learning experiences developed with different styles during an academic semester in two universities. The objective of the study has been to test the advantages of the blended style of learning, in terms of students' participation and initiative in the learning process, compared with those of pure virtual e-learning. The study shows how information technologies act as an incentive to improve students' participation during traditional classroom-located teaching, but do not help to increase their participation when the learning process is completely virtual and not complemented by regular classes.
Evolutionary Gabor Filter Optimization with Application to Vehicle Detection
Authors: Zehang Sun, George Bebis, Ronald Miller
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

Despite the considerable amount of research work on the applicationof Gabor filters in pattern classification, their design and selectionhave been mostly done on a trial and error basis. Existing techniques areeither only suitable for a small number of filters or less problem-oriented.A systematic and general evolutionary Gabor filter optimization (EGFO)approach that yields a more optimal, problem-specific, set of filters is proposedin this study. The EGFO approach unifies filter design with filter selectionby integrating Genetic Algorithms (GAs) with an incremental clusteringapproach. Specifically, filter design is performed using GAs, a globaloptimization approach that encodes the parameters of the Gabor filters ina chromosome and uses genetic operators to optimize them. Filter selectionis performed by grouping together filters having similar characteristics(i.e., similar parameters) using incremental clustering in the parameterspace. Each group of filters is represented by a single filter whose parameterscorrespond to the average parameters of the filters in the group. Thisstep eliminates redundant filters, leading to a compact, optimized set of filters.The average filters are evaluated using an application-oriented fitnesscriterion based on Support Vector Machines (SVMs). To demonstrate theeffectiveness of the proposed framework, we have considered the challengingproblem of vehicle detection from gray-scale images. Our experimentalresults illustrate that the set of Gabor filters, specifically optimized for theproblem of vehicle detection, yield better performance than using traditionalfilter banks.
Challenges in the Design of Embedded Real-time DSP SoCs
Authors: Mahesh Mehendale
Venue: Proceedings of the 17th International Conference on VLSI Design (2004)

This paper focuses on the challenges in the design ofembedded real-time DSP SoCs. We first present a genericmicroarchitecture of an SoC based on a programmableDSP CPU. We then discuss customer requirements for atypical SoC and present SoC design as a multidimensionaloptimization problem. We highlight the need to look at thedesign objectives in the context of the complete solutionand not just the chip. The paper looks at the challenges inboth the SoC definition and the design phases. We proposea concurrent engineering approach for SoC definition anda platform based approach for SoC design. The paper usesDM642 programmable digital media processor SoC as anexample to illustrate these approaches.
Rethinking Java strings
Authors: Paolo Boldi, Sebastiano Vigna
Venue: Proceedings of the 2nd international conference on Principles and practice of programming in Java (2003)

The Java string classes, String and StringBuffer, lie at the extremes of a spectrum (immutable, reference-based and mutable, content-based). Motivated by data-intensive text applications, we propose a new string class, MutableString, which tries to embody the best of both approaches.
Adaptive Coherency Maintenance Techniques for Time-Varying Data
Authors: Ratul kr. Majumdar, Kannan M. Moudgalya, Krithi Ramamritham
Venue: Proceedings of the 24th IEEE International Real-Time Systems Symposium (2003)

Often, data used in on-line decision making (for example,in determining how to react to changes in process behavior,traffic flow control, etc.) is dynamic in nature andhence the timeliness of the data delivered to the decisionmaking process becomes very important. The delivereddata must conform to certain time or value based applicationspecific inconsistency bounds. A system designedto disseminate dynamic data can exploit user-specified coherencyrequirements by fetching and disseminating onlythose changes that are of interest to users and ignoringintermediate changes. But, the design of mechanisms forsuch data delivery is challenging given that dynamic datachanges rapidly and unpredictably, the latter making it veryhard to use simple prediction techniques. In this paper, weaddress these challenges. Specifically, we develop mechanismsto obtain timely and consistency-preserving updatesfor dynamic data by pulling data from the source at strategicallychosen points in time. Motivated by the need forpractical system design, but using formal analytical techniques,we offer a systematic approach based on control-theoreticprinciples. Our solution is also unique from acontrol-theoretic perspective due to the presence of inherentnon-linear system components and the dependence betweenthe sampled time and sampled value. A proportional controllerwith dynamically changing tuning criteria is used inthis work as a means of deciding when to next refresh datafrom the source. Using real-world traces of real-time datawe show the superior performance of our feedback-drivencontrol-theoretic approach by comparing with (i) a previouslyproposed adaptive refresh technique and (ii) a newpattern matching technique.
Convergence of alternating optimization
Authors: James C. Bezdek, Richard J. Hathaway
Venue: Neural, Parallel Scientific Computations (2003)

Let f : Rs → R be a real-valued function, and let x = (x1,...,xs)T ∈ Rs be partitioned into t subsets of non-overlapping variables as x = (X1,...,Xt)T, with Xi ∈ Rpi for i = 1,...,t, Σi=1tpi = s. Alternating optimization (AO) is an iterative procedure for minimizing f(x) = f(X1, X2,..., Xt) jointly over all variables by alternating restricted minimizations over the individual subsets of variables X1,...., Xt. Alternating optimization has been (more or less) studied and used in a wide variety of areas. Here a self-contained and general convergence theory is presented that is applicable to all partitionings of x. Under reasonable assumptions, the general AO approach is shown to be locally, q-linearly convergent, and to also exhibit a type of global convergence.
On the existence of subexponential parameterized algorithms
Authors: Liming Cai, David Juedes
Venue: Journal of Computer and System Sciences (2003)

The existence of subexponential-time parameterized algorithms is examined for various parameterized problems solvable in time O(2o(k)p(n)). It is shown that for each t ≥ 1, there are parameterized problems in FPT for which the existence of O(2o(k)p(n))-time parameterized algorithms implies the collapse of W[t] to FPT. Evidence is demonstrated that Max-SNP-hard optimization problems do not admit subexponential-time parameterized algorithms. In particular, it is shown that each Max-SNP-complete problem is solvable in time O(2o(k)p(n)) if and only if 3-SAT ∈ DTIME(2o(n)). These results are also applied to show evidence for the non-existence of O(2o(√k)p(n))-time parameterized algorithms for a number of other important problems such as Dominating Set, Vertex Cover, and Independent Set on planar graph instances.
Efficient Algorithms for Identifying the Minimum Leakage States in CMOS Combinational Logic
Authors: Kaviraj Chopra, Sarma B. K. Vrudhula, Sarvesh Bhardwaj
Venue: Proceedings of the 17th International Conference on VLSI Design (2004)

Power dissipation in CMOS circuits during inactiveperiods (static power) has become a significant part ofthe total power dissipation. This is particularly problematicfor portable, battery powered systems, which are oftenin standby mode for long periods. It is well known thatthe major component of static power dissipation is due tosubthreshold conduction. For individual gates, this leakagecan vary by an order of magnitude over the gate's inputstates. Consequently, one way to minimize the leakageis to drive the inputs of the circuit to a state at whichthe leakage is minimum. In this paper, we present a newapproach to identify all minimum leakage states. Themethod performs implicit enumeration based on integervalued decision diagrams. Since the search space for minimumleakage vector is exponential in the number of primaryinputs, the enumeration is done with respect to theminimum balanced cut of the digraph representation ofthe circuit. The algorithm was successfully tested on theISCAS85 and MCNC91 benchmark circuits.