ppxscal/embedding_network huggingface dataset:
A Method for the On-Line Use of Off-Line Derived Remappings ofIterative Automatic Target Recognition Tasks onto a Particular Class ofHeterogeneous Parallel Platforms
Authors: John R. Budenske Ranga S. Ramanujan, Howard Jay Siegel
Venue: The Journal of Supercomputing (1998)

This study focuses on a particular application domain (iterative automatic target recognition tasks) and an associated specific class of dedicated heterogeneous parallel hardware platforms. For the computational environment considered, a methodology is presented for the on-line operating system to decide heuristically whether to perform a remapping of the application onto the platform based on information generated from input data by the application during execution. If the decision is to remap, the operating system will be able to select a mapping, which is appropriate for the given state of the application, from a stored set of mappings that were previously derived with an off-line heuristic.
Ontological Versus Knowledge Engineering
Authors: D. B. Lenat
Venue: IEEE Transactions on Knowledge and Data Engineering (1989)

The author first discusses the difference between a knowledge base (KB) and a database (DB), which seems to hinge on the 'gray box' verses 'black box' nature of the entries. He then discusses the need for a huge KB to break today's bottleneck in intelligent systems, i.e. their brittleness when confronted by unforeseen problems. That same brittleness-the representation trap-is what prevents multiple expert systems from cooperating or even sharing rules. The author then considers the central question of the present work: How is the task of building a huge KB different from that of building n small KBs? It is shown that this leads into the realm of ontological engineering, and it is found that there is no single, elegant 'use-neutral' solution to the problem, at least not at present, but that a kind of variegated 'tool-box' approach might succeed.
The DASDBS Project: Objectives, Experiences, and Future Prospects
Authors: H. -J. Schek, H. -B. Paul, M. H. Scholl, G. Weikum
Venue: IEEE Transactions on Knowledge and Data Engineering (1990)

A retrospective of the Darmstadt database system project, also known as DASDBS, is presented. The project is aimed at providing data management support for advanced applications, such as geo-scientific information systems and office automation. Similar to the dichotomy of RSS and RDS in System R, a layered architectural approach was pursued: a storage management kernel serves as the lowest common denominator of the requirements of the various applications classes, and a family of application-oriented front-ends provides semantically richer functions on top of the kernel. The lessons that were learned from building the DASDBS system are discussed. Particular emphasis is placed on the following issues: the role of nested relations, the experiences with using object buffers for coupling the system with the programming-language environment and the learning process in implementing multilevel transactions.
Fundamentals of X Programming: Graphical User Interfaces and Beyond
Authors: Theodosios Pavlidis, Theo Pavlidis
Venue:  (1999)

:This book provides an overview of the X Window System, focusing on characteristics that have significant impact on the development of both application programs and widgets. The X is the dominant window system under Unix, and X servers are available for Microsoft Windows, thus enabling graphics over a network in the PC world. Special attention to applications that go beyond graphical user interfaces (GUIs), such as visualization and imaging programs; issues affecting video games; and designing widgets with a complex appearance. While the book does not assume previous knowledge of X, it is intended for experienced programmers, especially those who want to write programs that go beyond simple GUIs.
Effective VLSI Processor Architectures for HLL Computers: The RISC Approach
Authors: Beatrice Lazzerini
Venue: IEEE Micro (1989)

The design principles of reduced-instruction-set computer (RISC) architectures as they apply to VLSI implementation for high-level languages (HLLs) are presented. The nature of general-purpose HLL computations is discussed in terms of static and dynamic program measurements, and the HLL features that need efficient support are identified. CISC (complex-instruction-set computer) and RISC approaches to general-purpose HLL computers are outlined, the effects of instruction-set reduction on both code size and execution time are evaluated, and the delayed-jump concept is introduced. The Berkeley RISC architecture is presented as an example.
An analytical study of CANIT algorithm in TCP protocol
Authors: H. Benaboud, A. Berqia, N. Mikou
Venue: ACM SIGMETRICS Performance Evaluation Review (2002)

CANIT (Congestion Avoidance with Normalized Interval of Time) algorithm is a new policy for TCP congestion avoidance which is proposed in order to improve TCP fairness over long delay links. CANIT uses a new parameter refered to NIT (Normalized Interval of Time), which is the key of this algorithm. In former works, we showed by simulations of some configuration with various value of NIT parameter, that using our algorithm instead of the standard one, improves the TCP fairness as well as the utilisation of network ressources. In this work, we propose an analytical study and we give the basic equations in order to find the optimal value of NIT parameter which provides more fairness and better bandwidth utilisation.
The Nonlocal Newton Method for Convex Optimization Problems and Monotone Variational Inequalities
Authors: V. M. Panin, V. V. Skopetskii
Venue: Cybernetics and Systems Analysis (2002)

The nonlocal Newton method is developed for nonlinear problems of conditional convex optimization and monotone variational inequalities in a finite-dimensional space. The Newton direction vector is calculated from a solution of a linear-approximating variational inequality. A new penalty function is proposed to define a step length.
A New Family of Cyclic Difference Sets with Singer Parameters in Characteristic Three
Authors: K. T. Arasu, Kevin J. Player
Venue: Designs, Codes and Cryptography (2003)

We construct a new family of cyclic difference sets with parameters ((3d &minus; 1)/2, (3d &minus; 1 &minus; 1)/2, (3d &minus; 2 &minus; 1)/2) for each odd d. The difference sets are constructed with certain maps that form Jacobi sums. These new difference sets are similar to Maschietti's hyperoval difference sets, of the Segre type, in characteristic two. We conclude by calculating the 3-ranks of the new difference sets.
Depth Estimation from Image Structure
Authors: Antonio Torralba, Aude Oliva
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)

In the absence of cues for absolute depth measurements as binocular disparity, motion, or defocus, the absolute distance between the observer and a scene cannot be measured. The interpretation of shading, edges, and junctions may provide a 3D model of the scene but it will not provide information about the actual ¿scale¿ of the space. One possible source of information for absolute depth estimation is the image size of known objects. However, object recognition, under unconstrained conditions, remains difficult and unreliable for current computational approaches. Here, we propose a source of information for absolute depth estimation based on the whole scene structure that does not rely on specific objects. We demonstrate that, by recognizing the properties of the structures present in the image, we can infer the scale of the scene and, therefore, its absolute mean depth. We illustrate the interest in computing the mean depth of the scene with application to scene recognition and object detection.
Building Application Generators
Authors: J. Craig Cleaveland
Venue: IEEE Software (1988)

The development of application generators, which offer increased productivity through customized reusable software, is addressed. Their advantages and drawbacks are first discussed. They describe a method, called the dialogue-code generation system, for building application generators, and discuss its use for various projects. Unix tools for building application generators are briefly considered.
Interactive Optimization of 3D Shape and 2D Correspondence Using Multiple Geometric Constraints via POCS
Authors: Z. Sun, A. M. Tekalp, N. Navab, V. Ramesh
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)

The traditional approach of handling motion tracking and structure from motion (SFM) independently in successive steps exhibits inherent limitations in terms of achievable precision and incorporation of prior geometric constraints about the scene. This paper proposes a projections onto convex sets (POCS) framework for iterative refinement of the measurement matrix in the well-known factorization method to incorporate multiple geometric constraints about the scene, thereby improving the accuracy of both 2D feature point tracking and 3D structure estimates. Regularities in the scene, such as points on line and plane and parallel lines and planes, that can be interactively identified and marked at each POCS iteration, enforce rank and parallelism constraints on appropriately defined local measurement matrices, one for each constraint. The POCS framework allows for the integration of the information in each of these local measurement matrices into a single measurement matrix that is closest to the initial observed measurement matrix in Frobenius norm, which is then factored in the usual manner. Experimental results demonstrate that the proposed interactive POCS framework consistently improves both 2D correspondences and 3D shape/motion estimates and similar results can not be achieved by enforcing these constraints as either post or preprocessing.
Numerical simulation of the evolution of aquifer porosity and species concentrations during reactive transport
Authors: Jui-Sheng Chen, Chen-Wuing Liu
Venue: Computers Geosciences (2002)

While flowing through a porous medium, a reactive fluid dissolves minerals thereby increasing its porosity and ultimately the permeability. The reactive fluid flows preferentially into highly permeable zones, which are therefore dissolved most rapidly, producing a further preferential permeability enhancement. Thus, the reaction front may be unstable. However, other factors, such as diffusion, suppress the instability of a reaction front. This study presents a numerical model to evaluate the interactions between mechanisms that determine the shape of a reactive front. That is, a method is developed to solve a set of nonlinear equations coupled with fluid flow, species transport, and rock-fluid reactions and includes the effects of grain dissolution and the alteration of porosity and permeability due to mineral-fluid reactions. The numerical model enables us to evaluate how a dissolution reaction affects the porosity structure and fluid pressure variation, from which local Darcy flux can then be evaluated. In addition, the model is used to examine how upstream pressure gradient affects the morphological instability of the species concentrations and the aquifer porosity. Simulation results indicate that, although stable for small upstream pressure gradients, the growth of a planar front becomes unstable for large upstream ones. Moreover, the diffusive, advective and resultant species fluxes of both these mechanisms are computed and presented to further elucidate the behavior of the morphological instability for a planar concentration and porosity front that results from the interactions between diffusion and advection.
Simulation-based automatic generation of signomial and posynomial performance models for analog integrated circuit sizing
Authors: Walter Daems, Georges Gielen, Willy Sansen
Venue: Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design (2001)

This paper presents a method to automatically generate posynomial response surface models for the performance parameters of analog integrated circuits. The posynomial models enable the use of efficient geometric programming techniques for circuit sizing and optimization. To avoid manual derivation of approximate symbolic equations and subsequent casting to posynomial format, techniques from design of experiments and response surface modeling in combination with SPICE simulations are used to generate signomial and posynomial models in an automatic way. Attention is paid to estimating the relative 'goodness-of-fit' of the generated models. Experimental results allow to assess both the quality of the generated models as well as the strengths and the limitations of the presented approach.
Constructing Bayesian Networks for Medical Diagnosis from Incomplete and Partially Correct Statistics
Authors: Daniel Nikovski
Venue: IEEE Transactions on Knowledge and Data Engineering (2000)

The paper discusses several knowledge engineering techniques for the construction of Bayesian networks for medical diagnostics when the available numerical probabilistic information is incomplete or partially correct. This situation occurs often when epidemiological studies publish only indirect statistics and when significant unmodeled conditional dependence exists in the problem domain. While nothing can replace precise and complete probabilistic information, still a useful diagnostic system can be built with imperfect data by introducing domain-dependent constraints. We propose a solution to the problem of determining the combined influences of several diseases on a single test result from specificity and sensitivity data for individual diseases. We also demonstrate two techniques for dealing with unmodeled conditional dependencies in a diagnostic network. These techniques are discussed in the context of an effort to design a portable device for cardiac diagnosis and monitoring from multimodal signals.
An Efficient Path Computation Model for Hierarchically Structured Topographical Road Maps
Authors: Sungwon Jung, Sakti Pramanik
Venue: IEEE Transactions on Knowledge and Data Engineering (2002)

In this paper, we have developed a \big. HiTi\bigr. (Hierarchical MulTi) graph model for structuring large topographical road maps to speed up the minimum cost route computation. The \big. HiTi\bigr. graph model provides a novel approach to abstracting and structuring a topographical road map in a hierarchical fashion. We propose a new shortest path algorithm named \big. SPAH\bigr., which utilizes \big. HiTi\bigr. graph model of a topographical road map for its computation. We give the proof for the optimality of \big. SPAH\bigr.. Our performance analysis of \big. SPAH\bigr. on grid graphs showed that it significantly reduces the search space over existing methods. We also present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works on grid graphs. Within the \big. HiTi\bigr. graph framework, we also propose a parallel shortest path algorithm named \big. ISPAH\bigr.. Experimental results show that inter query shortest path problem provides more opportunity for scalable parallelism than the intra query shortest path problem.
Improving Quality With a Manufacturing Process
Authors: Ytzhak Levendel
Venue: IEEE Software (1991)

A model that patterns software manufacturing after hardware manufacturing is presented. The model introduces a testing and analysis station between each development phase. At each station, the incoming product is tested and failure data are analyzed and compared with the quality criteria used. The decision is then made whether to proceed to the next phase or repair the software. A case study showing how the model was applied to a back-end process is presented.
Limiting the Dangers of Intuitive Decision Making
Authors: Lorenzo Strigini
Venue: IEEE Software (1996)

New views of mature ideas on software and quality productivityWe scientists like to think that we bring objectivity to our work. But this month, Lorenzo Strigini shows us that subjectivity is inevitable, and that intuition should be used with great caution; we should follow his guidelines for careful use.¿Shari Lawrence-Pfleeger
Thermoelastic modeling of lithospheric uplift: a finite-difference numerical solution
Authors: Juan Homero Hinojosa, Kevin L. Mickus
Venue: Computers Geosciences (2002)

This paper describes HEATFLEX.FOR, a FORTRAN computer program designed to model the thermoelastic uplift of lithospheric regions. The program was written using a finite-difference approximation to the heat-transfer and elastic-flexure equations in a two-layer cylindrical plate. The amount of uplift is determined by the mechanical and thermal properties of the lithosphere, the heat flux at the base and lower sides of the lithosphere, and the duration of the applied heating. The program outputs the temperature and thermal anomaly fields within the model, the heat flow and thermoelastic uplift of the surface, the Bouguer gravity anomaly amplitude, and the elastic and thermal lithospheric thicknesses. These values can then be compared to known values to determine if a thermoelastic model is suitable for the tectonic environment being modeled. The program is demonstrated by modeling a portion of the uplift of the Colorado Plateau in the western United States.
Selective Search for Global Optimization of Zero or Small Residual Least-Squares Problems: A Numerical Study
Authors: L. Velázquez, G. N. Phillips,  Jr., R. A. Tapia, Y. Zhang
Venue: Computational Optimization and Applications (2001)

In this paper, we consider approximating global minima of zero or small residual, nonlinear least-squares problems. We propose a selective search approach based on the concept of selective minimization recently introduced in Zhang et al. (Technical Report TR99-12, Rice University, Department of Computational and Applied Mathematics MS-134, Houston, TX 77005, 1999). To test the viability of the proposed approach, we construct a simple implementation using a Levenberg-Marquardt type method combined with a multi-start scheme, and compare it with several existing global optimization techniques. Numerical experiments were performed on zero residual nonlinear least-squares problems chosen from structural biology applications and from the literature. On the problems of significant sizes, the performance of the new approach compared favorably with other tested methods, indicating that the new approach is promising for the intended class of problems.
Fully Embodied Conversational Avatars: Making Communicative Behaviors Autonomous
Authors: J. Cassell, H. Vilhjálmsson
Venue: Autonomous Agents and Multi-Agent Systems (1999)

Although avatars may resemble communicative interface agents, they have for the most part not profited from recent research into autonomous embodied conversational systems. In particular, even though avatars function within conversational environments (for example, chat or games), and even though they often resemble humans (with a head, hands, and a body) they are incapable of representing the kinds of knowledge that humans have about how to use the body during communication. Humans, however, do make extensive use of the visual channel for interaction management where many subtle and even involuntary cues are read from stance, gaze, and gesture. We argue that the modeling and animation of such fundamental behavior is crucial for the credibility and effectiveness of the virtual interaction in chat. By treating the avatar as a communicative agent, we propose a method to automate the animation of important communicative behavior, deriving from work in conversation and discourse theory. BodyChat is a system that allows users to communicate via text while their avatars automatically animate attention, salutations, turn taking, back-channel feedback, and facial expression. An evaluation shows that users found an avatar with autonomous conversational behaviors to be more natural than avatars whose behaviors they controlled, and to increase the perceived expressiveness of the conversation. Interestingly, users also felt that avatars with autonomous communicative behaviors provided a greater sense of user control.
Splitting and Merging Version Spaces to Learn Disjunctive Concepts
Authors: Tzung-Pei Hong, Shian-Shyong Tseng
Venue: IEEE Transactions on Knowledge and Data Engineering (1999)

We have modified the original version space strategy in order to learn disjunctive concepts incrementally and without saving past training instances. The algorithm time complexity is also analyzed, and its correctness is proven.
A New Approach for Visual Cryptography
Authors: Wen-Guey Tzeng, Chi-Ming Hu
Venue: Designs, Codes and Cryptography (2002)

Visual cryptography is to encrypt a secret image into some shares (transparencies) such that any qualified subset of the shares can recover the secret &ldquo;visually.&rdquo; The conventional definition requires that the revealed secret images are always darker than the backgrounds. We observed that this is not necessary, in particular, for the textual images.In this paper, we proposed an improved definition for visual cryptography based on our observation, in which the revealed images may be darker or lighter than the backgrounds. We studied properties and obtained bounds for visual cryptography schemes based on the new definition. We proposed methods to construct visual cryptography schemes based on the new definition. The experiments showed that visual cryptography schemes based on our definition indeed have better pixel expansion in average.
An Information Theoretic Approach to Rule Induction from Databases
Authors: P. Smyth, R. M. Goodman
Venue: IEEE Transactions on Knowledge and Data Engineering (1992)

An algorithm for the induction of rules from examples is introduced. The algorithm is novel in the sense that it not only learns rules for a given concept (classification), but it simultaneously learns rules relating multiple concepts. This type of learning, known as generalized rule induction, is considerably more general than existing algorithms, which tend to be classification oriented. Initially, it is focused on the problem of determining a quantitative, well-defined rule preference measure. In particular, a quantity called the J-measure is proposed as an information-theoretic alternative to existing approaches. The J-measure quantifies the information content of a rule or a hypothesis. The information theoretic origins of this measure are outlined, and its plausibility as a hypothesis preference measure is examined. The ITRULE algorithm, which uses the measure to learn a set of optimal rules from a set of data samples, is defined. Experimental results on real-world data are analyzed.