ppxscal/embedding_network huggingface dataset:
The Hardware Implementation of A Multi-resolution Combined Fuzzy Min-Max Classifier Chip
Authors: Y. Liang, S. Q. Fan, D. M. Jin
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2 (2006)

This paper presents the design and implementation of a multi-resolution combined fuzzy neural network classifier. To improve classification speed, a parallel structure is developed for the classifier. The classifier presented consists of 4 parallel classification logic units, each of which has the same structure and functions, so that the classification logic units can operate classification simultaneously and obtain results at the same time. The classifier is realized using field programmable gate array (FPGA) and application specific integrated circuit (ASIC). Test results show that the maximal operation frequency is 100MHz and the chip can be cascaded to achieve high speed classification.
A Dynamic Classifier Selection Method to Build Ensembles using Accuracy and Diversity
Authors: Alixandre Santana, Rodrigo G. F. Soares, Anne M. P. Canuto, Marcilio C. P. de Souto
Venue: Proceedings of the Ninth Brazilian Symposium on Neural Networks (2006)

Ensemble of classifiers is an effective way of improving performance of individual classifiers. However, the choice of the ensemble members can become a very difficult task, in which, in some cases, it can lead to ensembles with no performance improvement. In order to avoid this situation, there is a need to find effective classifier member selection methods. In this paper, a DCS (Dynamic Classifier Selection)-based method is presented, which takes into account performance and diversity of the classifiers in order to choose the ensemble members.
TinkerNet: a low-cost and ready-to-deploy networking laboratory platform
Authors: Titus Winters, Ryan Ausanka-Crues, Mark Kegel, Erik Shimshock, Daniel Turner, Mike Erlinger
Venue: Proceedings of the 8th Austalian conference on Computing education - Volume 52 (2006)

TinkerNet1 was developed as a low-cost platform for teaching bottom-up, hands-on networking at the undergraduate level. Using "throw away" PCs, cheap components, and free software, TinkerNet enables students to build their own networking stack from Ethernet up to TCP or UDP, and to have their packets actually transmitted on the wire. Since nothing is emulated, standard networking tools such as packet sniffers may be used to test student generated traffic from a host located on the TinkerNet network. Over the past summer TinkerNet has matured and advanced thanks to an NSF deployment grant. This paper discusses TinkerNet design, development, and availability.
Behaviosites: a novel paradigm for affecting distributed behavior
Authors: Amit Shabtay, Zinovi Rabinovich, Jeffrey S. Rosenschein
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

We present the Behaviosite paradigm, a new approach to affecting the behavior of distributed agents in a multiagent system, which is inspired by biological parasites with behavior manipulation properties. Behaviosites are special kinds of agents that "infect" a system composed of agents operating in that environment. The behaviosites facilitate behavioral changes in agents to achieve altered, potentially improved, performance of the overall system. Behaviosites need to be designed so that they are intimately familiar with the internal workings of the environment and of the agents operating within it, and behaviosites apply this knowledge for their manipulation, using various infection and manipulation strategies. To demonstrate and test this paradigm, we implemented a version of the El Farol problem, using behaviosites.
Research Based on Fuzzy Algorithm of Cancer Cells in Pleural Fluid Microscopic Images Recognition
Authors: Lei Zhang, Qiuguang Wang, Jiping Qi
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

This paper introduces a kind of cancer cells in pleural fluid microscopic images processing and fuzzy recognizing method. We propose a method, which firstly segments the image using the OTSU thresholding method and fuzzy edge detection, then extracts 7 measurement parameters i.e. the area rate of the karyon and cytoplasm, the optic density, the shape factor and else, finally uses fuzzy pattern recognition which is based on establishing 6 membership functions and 4 normative modes to recognize the cancer cells. Experiments show that this system provides valuable suggestions to the diagnosis of cancer.
A Model-Driven Development Framework for Non-Functional Aspects in Service Oriented Grids
Authors: Hiroshi Wada, Junichi Suzuki, Katsuya Oba
Venue: Proceedings of the International Conference on Autonomic and Autonomous Systems (2006)

Service-oriented grids are grid computing systems built with the notion of service-oriented architecture (SOA). Using two major abstract concepts, services and connections between services, each grid application is designed as a collection of looselycoupled services in an implementation independent manner. In service-oriented grids, the non-functional aspects of services and connections (e.g., message transmission and security) should be described separately from their functional aspects because different applications use services and connections in different nonfunctional requirements. This paper presents a UML profile to graphically specify and maintain non-functional aspects in service-oriented grids as implementation independent UML models. The UML models are transformed into implementation specific code by a model-driven development tool. This paper demonstrates how the proposed UML profile is used in model-driven development of service-oriented grid applications.
Multi-dimensional Dependency and Conflict Resolution for Self-adaptable Context-aware Systems
Authors: Davy Preuveneers, Yolande Berbers
Venue: Proceedings of the International Conference on Autonomic and Autonomous Systems (2006)

Self-adaptable systems dynamically adapt to satisfy new functionality requirements, to optimize performance and to adapt to variable runtime conditions. Context-aware systems acquire and utilize information about the context of a user and a device to provide personalized applications. Adaptation in a transparent way for the user is an important concern for both systems. To decrease the adaptation complexity of self-adaptable context-aware systems, we propose to model self-adaptation across three layers of abstractions: the runtime infrastructure, the context middleware and the user applications. The aim is to achieve per layer selfadaptation of the composition or behavior of these layers without jeopardizing the integrity and usability of the overall system. We discuss a multi-dimensional dependency and conflict resolution mechanism to guide self-adaptation and find a stable reconfiguration of the system at runtime.
A Neural Model of Perceptual-Motor Alignment
Authors: Emmanuel Guigon, Pierre Baraduc
Venue: Journal of Cognitive Neuroscience (2002)

Sensorimotor systems face complex and frequent discrepancies among spatial modalities, for example, growth, optical distortion, and telemanipulation. Adaptive mechanisms must act continuously to restore perceptual-motor alignments necessary for perception of a coherent world. Experimental manipulations that exposed participants to localized discrepancies showed that adaptation is revealed by the acquisition of a constrained relation between entire modalities rather than associations between individual exemplars within these modalities. The computational problem faced by the human nervous system can thus be conceived as having to induce constrained relations between continuous stimulus and response dimensions from ambiguous or incomplete training sets, that is, performing interpolation and extrapolation. How biological neuronal networks solve this problem is unknown. Here we show that neural processing based on linear collective computation and least-square (LS) error learning in populations of frequency-coded neurons (i.e., whose discharge varies in a monotonic fashion with a parameter) has built-in interpolation and extrapolation capacities. This model can account for the properties of perceptual-motor adaptations in sensorimotor systems.
A new method for adaptive wideband beamforming
Authors: R. DeLap, A. Hero
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04 (1993)

Classical angle of arrival (AOA) estimation methods assume incoming signals are either purely narrowband or purely wideband in nature. There are many physical scenarios where this may not be the case. The authors call such scenarios mixed, in that the incoming signals contain a combination of both wideband and narrowband components. They introduce a new method for performing AOA estimation using a wideband adaptive beamsummer in the presence of mixed (narrowband and wideband) signals. The method uses an adaption criterion which is a function of both the mean and variance of the beamsummer output. The method is an extension of a similar narrowband beamsummer method (ICASSP1992 vol.4, p.461-4). Simulation results are presented which compare the performance of the new criterion with the standard narrowband and wideband adaptation criteria. These results show that the new method can perform as well or better than the classical methods in terms of target resolution and angle of arrival estimator variance.
How do we see?: information architecture as theory
Authors: Philip J. Piety, Annemarie Sullivan Palincsar
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Advanced digital technologies present both new types of texts and learning environments for learning scientists to study. These same technologies also support new ways of capturing and analyzing information on student thinking. This paper reports on research that used a digital learning environment (complete with prose, graphics, animations, and agents) to provide elementary school readers a scientific text containing embedded free-response assessment items to capture information on their thought processes. This paper explores methodological issues associated with coding and analyzing constructed response items of this type. Drawing on established approaches to propositional analysis with extensions to reflect the multimodal nature of the text and the task, we present a methodological approach developed to balance detail and nuance in students' use of language with a systematized approach to analyzing those data. This discussion is presented for both its value to the learning sciences and as a contribution to critical discussions about assessing student learning in complex learning environments.
Geometric filtering of pairwise atomic interactions applied to the design of efficient statistical potentials
Authors: Afra Zomorodian, Leonidas Guibas, Patrice Koehl
Venue: Computer Aided Geometric Design (2006)

Distance-dependent, pairwise, statistical potentials are based on the concept that the packing observed in known protein structures can be used as a reference for comparing different 3D models for a protein. Here, packing refers to the set of all pairs of atoms in the molecule. Among all methods developed to assess three-dimensional models, statistical potentials are subject both to praise for their power of discrimination, and to criticism for the weaknesses of their theoretical foundations. Classical derivations of pairwise potentials assume statistical independence of all pairs of atoms. This assumption, however, is not valid in general. We show that we can filter the list of all interactions in a protein to generate a much smaller subset of pairs that retains most of the structural information contained in proteins. The filter is based on a geometric method called alpha shapes that captures the packing in a conformation. Statistical scoring functions derived from such subsets perform as well as scoring functions derived from the set of all pairwise interactions.
Engineering girls gone wild: developing an engineering identity in digital zoo
Authors: Gina Navoa Svarovsky, David Williamson Shaffer
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

In the Digital Zoo epistemic game, middle school girls work as engineers to design virtual, ambulatory creatures. The activities of the game were based on an ethnographic study of an undergraduate engineering design course. As a result of gameplay, the girls demonstrated an increase in thinking of themselves as engineers. Moreover, both the girls and undergraduates linked their engineering identity development to meeting with -- and getting feedback from -- external clients and experts.
Restoration of scanned photographic images
Authors: S. Ibrahim Sadhar, A. N. Rajagopalan
Venue: Signal Processing (2006)

In this paper, we address the problem of restoring photographic images degraded by motion blur and film-grain noise. Based on the one-dimensional particle filter, a new approach is proposed for restoration under space-invariant as well as space-variant blurring conditions. The method works by propagating the samples of the probability distribution through an appropriate state model. The weights of the samples are computed using the observation model and the degraded image. The samples and their corresponding weights are used to estimate the original image. In order to verify and validate the proposed approach, the method is tested on several images, both synthetic and real.
A framework for the analysis of software cost estimation accuracy
Authors: Stein Grimstad, Magne Jørgensen
Venue: Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering (2006)

Many software companies track and analyze project performance by measuring cost estimation accuracy. A high estimation error is frequently interpreted as poor estimation skills. This is not necessarily a correct interpretation. High estimation error can also be a result of other factors, such as high estimation complexity and insufficient cost control of the project. Through a real-life example we illustrate how the lack of proper estimation error analysis technique can bias analyses of cost estimation accuracy and lead to wrong conclusions. Further, we examine a selection of cost estimation studies, and show that they frequently do not take the necessary actions to ensure meaningful interpretations of estimation error data. Motivated by these results, we propose a general framework that, we believe, will improve analyses of software cost estimation error.
Support vector machines in A+
Authors: Alexander Skomorokhov, Alexander Nakhabov
Venue: ACM SIGAPL APL Quote Quad (2004)

This paper considers the implementation of Support Vector Machines (SVM), the new extensive class of data analysis methods. SVM have a number of advantages as compared with standard data mining techniques like artificial neural networks, for example. In the paper this methodology is described in details and implemented in A+ programming language in the step-by-step fashion.
An Ontology Mapping Method Based on Tree Structure
Authors: Sheng Li, Heping Hu, Xian Hu
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

This paper provides an approach for ontology mapping based on tree structure grammar. Its excellence is that it combines both the similarity of the inner structure of concepts in different ontologies and the language similarity of concepts. In this way, more potential relationship between concepts could be found, and the validity of the calculation of similarity could be improved.
Unacceptability of instantaneous errors in mobile television: from annoying audio to video
Authors: Satu Jumisko-Pyykkö, Vinod Kumar M. V., Jari Korhonen
Venue: Proceedings of the 8th conference on Human-computer interaction with mobile devices and services (2006)

As in many digital telecommunications systems, the received data streams over Digital Video Broadcasting for Handhelds (DVB-H) may contain bursty transmission errors. The bursty error characteristics affect the end users' perceived audiovisual quality. This study examined the perceived unacceptability of instantaneous but noticeable audio, visual and audiovisual errors. The erroneous streams were generated from four popular television contents by applying three simulated error patterns with different error rates (1.7%, 6.9%, 13.8%) and error burst durations. Instantaneous unacceptability of errors was evaluated by 30 participants with simplified continuous assessment while watching the program content. The results show that with the two lowest error rates the audio errors were more unacceptable than video errors and with the highest error rate the visual and audiovisual errors become the most unacceptable.
MRF's forMRI's: Bayesian Reconstruction of MR Images via Graph Cuts
Authors: Ashish Raj, Gurmeet Singh, Ramin Zabih
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Markov Random Fields (MRF's) are an effective way to impose spatial smoothness in computer vision. We describe an application of MRF's to a non-traditional but important problem in medical imaging: the reconstruction of MR images from raw fourier data. This can be formulated as a linear inverse problem, where the goal is to find a spatially smooth solution while permitting discontinuities. Although it is easy to apply MRF's to the MR reconstruction problem, the resulting energy minimization problem poses some interesting challenges. It lies outside of the class of energy functions that can be straightforwardlyminimized with graph cuts. We show how graph cuts can nonetheless be adapted to solve this problem, and provide some theoretical analysis of the properties of our algorithm. Experimentally, our method gives very strong performance, with a substantial improvement in SNR when compared with widely-used methods for MR reconstruction.
Image Robust Hashing Based on DCT Sign
Authors: Longjiang Yu, Shenghe Sun
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

Image robust hashing is related to cryptographic hash functions. In contrast to cryptographic hash functions this robust digest is sensitive only to perceptual change. Minor changes, which are not affecting the perception, do not result in a different hash. Image robust hashing is used in content-based retrieval, monitoring, and filtering. In this paper an image robust hashing method based on sign bit from the domain of Discrete Cosine Transform (DCT) is presented. DCT is widely used in image processing and video processing, e.g. for compression or digital watermarking. From an image with reduced dimensions we apply 2-D DCT to derive an initial feature vector. The sign bit of this feature vector is extracted to form an intermediate hash. The intermediate hash can be incorporated into some security mechanism to derive a final hash. The advantages of the sign signal in DCT domain are verified in experiments evaluating robustness (e.g. against operations like lossy compression, scaling and cropping) and discriminability. The results show a better performance of the proposed method in this paper than an existing method.
Classifications of Dense Languages
Authors: Zheng-Zhu Li, H. J. Shyr, Y. S. Tsai
Venue: Acta Informatica (2006)

Let X be a finite alphabet containing more than one letter. A dense language over X is a language containing a disjunctive language. A language L is an n-dense language if for any distinct n words $$w_1, w_2, \ldots,w_n \in X^+,$$ there exist two words $$u, v \in X^*$$ such that $$uw_1v, uw_2v, \ldots uw_nv \in L.$$ In this paper we classify dense languages into strict n-dense languages and study some of their algebraic properties. We show that for each n &#x00a0;&#x2265;&#x00a0; 0, the n-dense language exists. For an n-dense language L, n &#x00a0;&#x2260;&#x00a0; 1, the language L &#x2229; Q is a dense language, where Q is the set of all primitive words over X. Moreover, for a given n &#x00a0;&#x2265;&#x00a0; 1, the language L is such that $$L \cap Q\in D_n(X)$$, then $$L\in D_m(X)$$ for some m, n &#x00a0;&#x2264;&#x00a0; m &#x00a0;&#x2264;&#x00a0; 2n&#x00a0;+&#x00a0;1. Characterizations on 0-dense languages and n-dense languages are obtained. It is true that for any dense language L, there exist $$w_1\neq w_2\in X^+$$ such that $$uw_1v,uw_2v\in L$$ for some $$u,v\in X^\ast$$. We show that everyn-dense language, n&#x00a0;&#x2265;&#x00a0; 0, can be split into disjoint union of infinitely many n-dense languages.
Aligning IT components to achieve agility in globally distributed system development
Authors: One-Ki (Daniel) Lee, Probir Banerjee, Kai H. Lim, Kuldeep Kumar, Jos van Hillegersberg, Kwok Kee Wei
Venue: Communications of the ACM (2006)

Agile IT strategy, infrastructure, and project management are key elements for realizing agility in GDSD projects.
On the efficient use of video-on-demand storage facility
Authors: Jun Guo, P. Taylor, M. Zukerman, S. Chan, K. S. Tang, E. W. M. Wong
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

We consider a video-on-demand system in which multiple copies of each movie file are kept in separate disks. Various schemes for file allocation and retrieval are considered and compared. We have introduced a certain easy-to-implement scheme that requires 15% more storage than another certain harder-to-implement scheme.
New measures of robustness in rare event simulation
Authors: Hector Cancela, Gerardo Rubino, Bruno Tuffin
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Rare event simulation requires acceleration techniques in order to i) observe the rare event and ii) obtain a valid and small confidence interval for the expected value. A "good" estimator has to be robust when rarity increases. This paper aims at studying robustness measures, the standard ones in the literature being Bounded Relative Error and Bounded Normal Approximation. By considering the problem of estimating the reliability of a static model for which simulation time per run is the critical issue, we show that actually those measures do not validate the satisfying behavior of some techniques. We thus define Bounded Relative Efficiency and generalized bounded normal approximation properties of the two previous measures in order to encompass the simulation time. We also illustrate how a user can have a look at the coverage of the resulting confidence interval by using the so-called coverage function.
Informatics Acquisition by Sterling Software: Unsolicited Offer, Takeover Attempt, and Merger
Authors: Walter F. Bauer
Venue: IEEE Annals of the History of Computing (2006)

A series of events began in 1983 that eventually led to Sterling Software's 1985 acquisition ofInformatics. The acquisition, unique at the time in the software industry, was preceded by anunsolicited offer and takeover attempt with a proxy fight. The transaction might well be called a"hostile takeover" although Informatics finally accepted the merger terms.