ppxscal/embedding_network huggingface dataset:
Interoperability among CAD/CAM/CAE Systems: A Review of Current Research Trends
Authors: Francesco Bianconi, Paolo Conti, Luca Di Angelo
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

Interoperability among CAD/CAM/CAE systems is a well known problem in product design and development. At present geometrical data exchange among different software packages is usually carried out through neutral file formats (IGES or STEP) or through proprietary formats. Data exchange processes are usually afflicted by several problems, such as: information loss, redundancy, one-way data exchange and static data exchange. These drawbacks do not permit a really geometric-centric design, and even if the model is transmitted without loss of information, the exchanged data do not incorporate details such as sketches, constraints and features, which represent the designer's intent. As a result, the model can hardly be modified, and the original intent of the designer may be misunderstood. During the last five years various solutions have been proposed to solve the above mentioned problems. The aim of this work is to investigate and discuss recent research trends in this topic.
fMRI Evidence for Separable and Lateralized Prefrontal Memory Monitoring Processes
Authors: Ian G. Dobbins
Venue: Journal of Cognitive Neuroscience (2004)

Source memory research suggests that attempting to remember specific contextual aspects surrounding prior stimulus encounters results in greater left prefrontal cortex (PFC) activity than simple item-based old/new recognition judgments. Here, we tested a complementary hypothesis that predicts increases in the right PFC with tasks requiring close monitoring of item familiarity. More specifically, we compared a judgment of frequency (JOF) task to an item memory task, in which the former required estimating the number of previous picture encounters and the latter required discriminating old from new exemplars of previously seen items. In comparison to standard old/new recognition, both source memory and the JOF task examined here require more precise mnemonic judgments. However, in contrast to source memory, cognitive models suggest the JOF task relies heavily upon item familiarity, not specific contextual recollections. Event-related fMRI demonstrated greater recruitment of right, not left, dorsolateral and frontopolar PFC regions during the JOF compared to item memory task. These data suggest a role for right PFC in the close monitoring of the familiarity of objects, which becomes critical when contextual recollection is ineffective in satisfying a memory demand.
Lightweight fusion by fixed point promotion
Authors: Atsushi Ohori, Isao Sasano
Venue: Proceedings of the 34th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2007)

This paper proposes a lightweight fusion method for general recursive function definitions. Compared with existing proposals, our method has several significant practical features: it works for general recursive functions on general algebraic data types; it does not produce extra runtime overhea (except for possible code size increase due to the success of fusion); and it is readily incorporated in standard inlining optimization. This is achieved by extending the ordinary inlining process with a new fusion law that transforms a term of the form f o (fixgλx.E) to a new fixed point term fixhλx.E′ by promoting the function f through the fixed point operator. This is a sound syntactic transformation rule that is not sensitive to the types of f and g. This property makes our method applicable to wide range of functions including those with multi-parameters in both curried and uncurried forms. Although this method does not guarantee any form of completeness, it fuses typical examples discussed in the literature and others that involve accumulating parameters, either in the tt foldl-like specific forms or in general recursive forms, without any additional machinery. In order to substantiate our claim, we have implemented our method in a compiler. Although it is preliminary, it demonstrates practical feasibility of this method.
Learning objects, places and relations in a brain model of visual navigation
Authors: Michael A. Arbib
Venue:  (2005)

In the last fifty years a significant amount of research has been devoted to the analysis of the different processes that may lead to intelligent behavior. Although very exciting achievements have resulted from this effort, their success has been limited by their specificity. Generally, the fitness of artificial systems is restricted to the data the system has been trained or designed for. With results getting significantly worse when the test is performed on a different domain or data. So, models of visual recognition will fail when changes to illumination or pose are applied, as language understanding systems do when tested in an unfamiliar language domain. This thesis makes the claim that learning is an essential component of intelligent behavior. Given the enormous complexity of our world, it is unrealistic to manually incorporate all the knowledge required by an artificial system to succeed under general conditions. Rather, some mechanisms should be put in place to learn from interaction with the environment. The thesis takes as example the problem of visually guided navigation. The goal is to optimize the interaction with the environment, so that interesting places (like those containing food or water) are quickly located, while dangerous places are avoided. For that purpose, two main objectives should be met. First the system should be able to extract knowledge about the environment, like what are the common relationships held by the different stimuli in the environment. Second, the acquired knowledge should be used to improve the interaction by establishing predictions about subsequent states of the environment. The work follows a biological inspiration and so various hypotheses and insights about the physiology of the brain are drawn. The model presented shows how knowledge about objects, places and their relationships can be extracted from visually experiencing an environment and how this information can be encoded in a biologically-plausible neural architecture. Similarly, mechanisms are proposed whereby the acquired knowledge is used to focus attention and facilitate recognition based on top-down expectations, thereby improving the interaction of the subject with the external world.
Adaptive channel equalization for TDMA digital cellular communications using antenna arrays
Authors: A. F. Naguib, B. Khalaj, A. Paulraj, T. Kailath
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Mobile radio channels can be generally characterized as a fading multipath channel with multipath spread delay that ranges from a few microseconds (/spl mu/s) up to as much as 15 /spl mu/s. Such large delays result in intersymbol interference which raises the need for equalization. A semi-blind maximum likelihood sequence estimation (MLSE) with an antenna array is studied as an adaptive equalization method for time division multiple access (TDMA) digital cellular systems. The MLSE is implemented using a Viterbi algorithm (VA). An antenna array is used to utilize both temporal and spatial structure in the received signal to provide the VA with the estimate of the channel impulse response necessary for it to perform MLSE.
Fast random number generators based on linear recurrences modulo 2: overview and comparison
Authors: Pierre L'Ecuyer, François Panneton
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Random number generators based on linear recurrences modulo 2 are among the fastest long-period generators currently available. The uniformity and independence of the points they produce, over their entire period length, can be measured by theoretical figures of merit that are easy to compute, and those having good values for these figures of merit are statistically reliable in general. Some of these generators can also provide disjoint streams and substreams efficiently. In this paper, we review the most interesting construction methods for these generators, examine their theoretical and empirical properties, and make comparisons.
Combined spatial and temporal equalization using an adaptive antenna array and a decision feedback equalization scheme
Authors: E. Lindskog, A. Ahlen, M. Sternad
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

The purpose of this paper is to investigate the use of combined spatial and temporal equalization, in particular for short training sequences. The motivation for combining spatial and temporal equalization is the existence of multipath propagation and co-channel interference. Our main concern is to obtain good performance yet low complexity. We will suggest a low complexity algorithm utilizing a circular antenna array. Although it has inferior performance in an asymptotic sense, it turns out to be superior to the general solution for short training sequences. This conclusion is supported by simulations where a number of algorithms are evaluated for different scenarios involving co-channel interference.
Branching into Cosmic Unity
Authors: Gary Singh
Venue: IEEE Computer Graphics and Applications (2006)

Valeriy Grachov creates both abstract and representational digital works using such programs as Corel Painter, Adobe Photoshop, and Alien Skin Eye Candy 4000.
Simultaneous training of fuzziness generator and inference rules in the freehand curve identifier FSCI
Authors: Motoaki Oguma, Hiroyasu Takikawa, Sato Saga
Venue: Systems and Computers in Japan (2007)

Freehand curve recognition method FSCI is already proposed and consists of the following procedure. The freehand drawing is represented as a fuzzy curve model by using a fuzziness generator, and fuzzy inference is used to find as simple a geometrical curve as possible, so that the drawing intention of the user is identified. It is recognized that the adequacy of the parameter setting in the fuzziness generator and the inference rules has a serious effect on the identification performance of FSCI. Thus, training optimization for the fuzziness generator using the genetic algorithm, and training optimization of inference rules using a neural network have been separately proposed. This paper proposes a new method which achieves simultaneous training optimization of the fuzziness generator and the inference rules using a neural network. The effectiveness of the method is demonstrated experimentally. &copy; 2006 Wiley Periodicals, Inc. Syst Comp Jpn, 38(1): 51&ndash; 61, 2007; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.10387.
Showing evidence: analysis of students' arguments in a range of settings
Authors: Issam Abi-El-Mona, Barbara Hug
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

The purpose of this study is to investigate evidence-based arguments generated through the use of a web based tool, Showing Evidence. Six of 40 sample classrooms during 2004-2005 were purposefully sampled from the tool's database. Analysis focused on identifying the physical and argumentation schematic structures of possible evidence based explanations using Toulmin (1958) and Walton (1996) frameworks. Findings demonstrate student's ability to depict proper data for claims yet inability in structuring overall explanations.
A Characterization of UML Diagrams and their Consistency
Authors: Xiaoshan Li
Venue: Proceedings of the 11th IEEE International Conference on Engineering of Complex Computer Systems (2006)

In this paper, we focus on giving a formal semantics of sequence diagram of UML2.0. A model of a system comprises a set of program variables, a class diagram, a family of normal sequence diagrams, a family of normal state diagrams, and a state constraint. We then define their static and dynamic consistency supported by the formal semantics.
Learning to program in java using robots
Authors: Diane Mcgrath
Venue:  (2006)

This dissertation is a case study of class that used Lego&reg; Mindstorms&trade; robots to facilitate learning the computer language Java. The class participants were elementary and middle school, in-service teachers. The class was funded by a grant from the National Science Foundation/Research Experience for Teachers program. The study was prompted by the lack of research on teaching computer programming. Since computer programming is vital to science and industry, this lack of study of the pedagogy of computer programming is troubling. If methods to improve introductory computer programming classes could be found, the impact on students would be large. The researcher on this project has almost 30 years of computer programming experience. During that time, he has observed that computer programming is a skill that is best taught in the context of accomplishing a goal that the student programmer wants to achieve. Current practice in most computer programming classes decontextualize the subject and provide little intrinsic motivation for the students. The current research hypothesizes that programming a robot to perform certain tasks, especially in the context of competition between students, i.e. playing a game, will motivate the students to want to learn to program. This intrinsic motivation will help keep the students on task during the learning process. There are two major assertions from this study. First, the robots did help the students learn to program in Java. Second, building self-confidence in the students is critical to having them become independent programmers. Additional findings are that building a community of student programmers encourages the formation of the needed self-confidence and that the students found that using the robots made programming fun.
Framework for Modeling Reordering Heuristics for Asynchronous Backtracking
Authors: Marius Calin Silaghi
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

Dynamic reordering of variables is known to be important for solving constraint satisfaction problems (CSPs). Efforts to apply this principle for improving polynomial space asynchronous backtracking (ABT) started with [1], using a solution based on synchronization points. [17] shows how to asynchronously enable reordering heuristics in ABT and proposes a general protocol called Asynchronous Backtracking with Reordering (ABTR). In this work we introduce a first framework for modeling heuristics possible with asynchronous backtracking. We also show that ABTR enables heuristics that displace even the agent requesting the reordering, as in the reordering of Dynamic Backtracking. They have not been illustrated in [17]. The most efficient self-reordering heuristic that we introduce and experiment, approx-AWC1, is inspired from AsynchronousWeak-Commitment [21] and brings small but significant improvements, comparable to the results in [1]. We also report that min-domain dynamic ordering heuristics for ABTR are worse than no reordering and better than max-domain (in experiments that also use maintenance of arc consistency).
Rate-distortion analysis of the multiple description motion compensation video coding scheme
Authors: Shunan Lin, A. Vetro, Yao Wang
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

Multiple description motion compensation (MDMC) is a multiple description video coding scheme that has shown good error resilience performance. MDMC enables one to vary coding parameters according to the desired trade-off between coding efficiency and error resilience. To fully utilize this advantage, one needs to establish a set of models, relating the rate, encoder distortion, and the end-to-end distortion after transmission, with the encoder parameters and channel parameters. Using these models, one can find the optimal coding parameters for given channel parameters and rate (or distortion) constraints. In this paper, we formulate and validate the rate and encoder distortion models.
Some researches on trivariate Lagrange interpolation
Authors: Xue-Zhang Liang, Ren-Hong Wang, Li-Hong Cui, Jie-Lin Zhang, Ming Zhang
Venue: Journal of Computational and Applied Mathematics (2006)

In this paper, in order to go a step further research on the problem of trivariate Lagrange interpolation, we pose the concepts of sufficient intersection of algebraic surfaces and Lagrange interpolation along a space algebraic curve, and extend Cayley-Bacharach theorem in algebraic geometry from R2 to R3. By using the conclusion of the extended theorem, we deduce a general method of constructing properly posed set of nodes for Lagrange interpolation along a space algebraic curve, and give a series of corollaries for the practical applications. Moreover, we give a new method of constructing properly posed set of nodes for Lagrange interpolation along an algebraic surface, and as a result we make clear the geometrical structure of it.
Positioning in Releasing Manipulation by Iterative Learning Control
Authors: Chi Zhu, Yasumichi Aiyama, Tamio Arai, Atsuo Kawamura
Venue: Journal of Intelligent and Robotic Systems (2006)

In order to improve the positioning precision of the stop posture (position and orientation) of an object and decrease the trial numbers in our proposed releasing manipulation, two iterative learning control (ILC) schemes, learning control based on convergent condition (LCBCC), and learning control based on optimal principle (LCBOP) are designed in experimental-oriented way. These two methods are all based on a linearized system model. The experimental results show that these methods are effective. Having discussed the characteristics of these control methods, we conclude that in the case there is no enough system knowledge, LCBCC is the only choice to be used to learn the system knowledge; after the enough experience has been acquired, LCBOP is better than LCBCC, in the view of both of the convergent rate and the precision.
Adaptive distributed monitoring with accuracy objectives
Authors: Alberto Gonzalez Prieto, Rolf Stadler
Venue: Proceedings of the 2006 SIGCOMM workshop on Internet network management (2006)

We present A-GAP, a novel protocol for continuous monitoring of network state variables, which aims at achieving a given monitoring accuracy with minimal overhead. Network state variables are computed from device counters using aggregation functions, such as SUM, AVERAGE and MAX. The accuracy objective is expressed as the average estimation error. A-GAP is decentralized and asynchronous to achieve robustness and scalability. It executes on an overlay that interconnects management processes on the devices. On this overlay, the protocol maintains a spanning tree and updates the network state variables through incremental aggregation. It dynamically configures local filters that control whether an update is sent towards the root of the tree. It reduces the overhead by attempting to minimize the maximum processing load over all management processes. We evaluate A-GAP through simulation using an ISP topology and real traces. The results show that we can effectively control the trade-off between accuracy and protocol overhead, that the overhead can be reduced significantly by allowing small errors, and that an accurate estimation of the error distribution can be provided in real-time.
A Context-based Ontological Structure for Knowledge Sharing and Customization
Authors: K. Kevin Deeb
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

Several research projects have recently surfaced to automate the discovery and acquisition of knowledge from information and to facilitate information sharing and reusability in the global network. However, some of these research attempts are limited in scope with respect to proper identification and delivery of customized information. This paper addresses some of these challenges by proposing a high-level ontological and context-based architecture that enables information customization and knowledge organization. The proposed model aims at managing knowledge items through the use of stand-alone computational layers. Ontology is used in this research to describe knowledge representation and structure, whereas context reflects knowledge adaptability to its hosting environment.
Enhanced Coercivity for Pure Advection and Advection---Diffusion Problems
Authors: Claudio Canuto
Venue: Journal of Scientific Computing (2006)

We present a common framework in which to set advection problems or advection---diffusion problems in the advection dominated regime, prior to any discretization. It allows one to obtain, in an easy way via enhanced coercivity, a bound on the advection derivative of the solution in a fractional norm of order ¿1/2. The same bound trivially applies to any Galerkin approximate solution, yielding a stability estimate which is uniform with respect to the diffusion parameter. The proposed formulation is discussed within Fourier methods and multilevel (wavelet) methods, for both steady and unsteady problems.
What Are We Arguing About? A Framework for Defining Agile in our Organization
Authors: Kelly Weyrauch
Venue: Proceedings of the conference on AGILE 2006 (2006)

How do we implement Agile? Is Agile a good thing for my organization? What barriers will I have to overcome? All of these are important questions when deciding whether and how to apply Agile Software Development to an organization that is used to working in a different way. To enable a good discussion, the language of that discussion must be established. As Medtronic adopted Agile, we realized how important it was to put effort into the language. We established a framework for that language, organizing our thoughts into three areas: Principles, Practices, and Benefits. When talking with visionaries or evangelists, we speak in terms of principles to understand why Agile is the way it is. With practitioners or pragmatists, we speak in terms of Practices to understand how to do Agile. With skeptics, we speak in terms of benefits to determine whether Agile is a good thing for us. In most cases, an effective conversation needs to address all three perspectives. The framework and language help us determine whether issues are related simply to communication barriers, or are related to the decisions of whether and how to apply Agile to our world.
Anti-collusion of group-oriented fingerprinting
Authors: Z. J. Wang, Min Wu, W. Trappe, K. J. R. Liu
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

Digital fingerprinting of multimedia data involves embedding information in the content, and offers protection to the digital rights of the content by allowing illegitimate usage of the content to be identified by authorized parties. One potential threat to fingerprints is collusion, whereby a group of adversaries combine their individual copies in an attempt to remove the underlying fingerprints. Former studies indicate that collusion attacks based on a few dozen independent copies can confound a fingerprinting system that employs orthogonal modulation. However, since an adversary is more likely to collude with some users than other users, we propose a group-based fingerprinting scheme where users likely to collude with each other are assigned correlated fingerprints. We evaluate the performance of our group-based fingerprints by studying the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints. We compare the results to those of fingerprinting systems employing orthogonal modulation.