ppxscal/embedding_network huggingface dataset:
Efficient fast recursive least-squares adaptive complex filtering using real valued arithmetic
Authors: George-Othon Glentis
Venue: Signal Processing (2005)

In this paper, a novel implementation of the fast recursive least squares (FRLS) algorithm for complex adaptive filtering, is presented. Complex signals are treated as pairs of real signals, and operations are re-organized on a real arithmetic basis. A new set of signals and filtering parameters is introduced, which are expressed either as the sum, or as the difference between the real and the imaginary part of the original variables. The algorithmic strength reduction technique is subsequently applied, resulting in significant computational savings. In this way, an efficient, FRLS algorithm is derived, where only two real valued filters are propagated, based on novel three-terms recursions for the time updating of the pertinent parameters. The proposed algorithm is implemented using real valued arithmetic only, whilst reducing the number of the required real valued multiplication operations by 23.5%, at the expense of a marginal 2.9% increase in the number of the real valued additions. The performance of the proposed FRLS algorithm is investigated by computer simulations, in the context of adaptive system identification and adaptive channel equalization.
Connections between subwords and certain matrix mappings
Authors: Arto Salomaa
Venue: Theoretical Computer Science (2005)

Parikh matrices recently introduced have turned out to be a powerful tool in the arithmetizing of the theory of words. In particular, many inequalities between (scattered) subword occurrences have been obtained as consequences of the properties of the matrices. This paper continues the investigation of Parikh matrices and subword occurrences. In particular, we study certain inequalities, as well as information about subword occurrences sufficient to determine the whole word uniquely. Some algebraic considerations, facts about forbidden subwords, as well as some open problems are also included.
EduBingo: A Bingo-like Game for Mathematics Skill Building
Authors: Mong-Chen Chiang, Yi-Chan Deng, Han-Zen Chang, Hui-Chun Liao, Chin-Wen Ho, Tak-Wai Chan
Venue: Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (2005)

Many students find mathematics difficult and do not like studying mathematics. Some researchers suggest that computer games can be highly effective in increasing children's learning and enjoyment of mathematics. In this paper, we described a bingo-like system for mathematics skill building. The main aim of the game is to increase the level of motivation and engagement of students during skill building. The functions and features of the system are presented in the paper and a preliminary study at an elementary school is also outlined and discussed.
On Curvatures and Focal Points of Distributions of Dynamical Lagrangian Distributions and their Reductions by First Integrals
Authors: A. A. Agrachev, N. N. Chtcherbakova, I. Zelenko
Venue: Journal of Dynamical and Control Systems (2005)

Pairs (Hamiltonian system, Lagrangian distribution) called dynamical Lagrangian distributions, appear naturally in differential geometry, calculus of variations, and rational mechanics. The basic differential invariants of a dynamical Lagrangian distribution with respect to the action of the group of symplectomorphisms of the ambient symplectic manifold are the curvature operator and curvature form. These invariants can be considered as generalizations of the classical curvature tensor in Riemannian geometry. In particular, in terms of these invariants one can localize the focal points along extremals of the corresponding variational problems. In the present paper we study the behavior of the curvature operator, the curvature form, and the focal points of a dynamical Lagrangian distribution after its reduction by arbitrary first integrals in involution. An interesting phenomenon is that the curvature form of so-called monotone increasing Lagrangian dynamical distributions, which appear naturally in mechanical systems, does not decrease after reduction. It also turns out that the set of focal points to the given point with respect to the monotone increasing dynamical Lagrangian distribution and the corresponding set of focal points with respect to its reduction by one integral are alternating sets on the corresponding integral curve of the Hamiltonian system of the considered dynamical distributions. Moreover, the first focal point corresponding to the reduced Lagrangian distribution comes before any focal point related to the original dynamical distribution. We illustrate our results on the classical N-body problem.
The Superconvergence of the Composite Trapezoidal Rule for Hadamard Finite Part Integrals
Authors: Jiming Wu, Weiwei Sun
Venue: Numerische Mathematik (2005)

The composite trapezoidal rule has been well studied and widely applied for numerical integrations and numerical solution of integral equations with smooth or weakly singular kernels. However, this quadrature rule has been less employed for Hadamard finite part integrals due to the fact that its global convergence rate for Hadamard finite part integrals with (p+1)-order singularity is p-order lower than that for the Riemann integrals in general. In this paper, we study the superconvergence of the composite trapezoidal rule for Hadamard finite part integrals with the second-order and the third-order singularity, respectively. We obtain superconvergence estimates at some special points and prove the uniqueness of the superconvergence points. Numerical experiments confirm our theoretical analysis and show that the composite trapezoidal rule is efficient for Hadamard finite part integrals by noting the superconvergence phenomenon.
Forecasting the Flow of Data Packets in Web Using ANFISCH Predictor Tuned by Segmented Adaptive Support Vector Regression
Authors: Bao Rong Chang
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

This study introduces a fast and accurate nonperiodic short-term predictor, ANFISNCH, as a specified web services for forecasting the flow of data packets between server and clients. Even though ANFIS is a fast fuzzy inference or predictor, the phenomenon of volatility clustering always generates the extreme outliers embedded in the training data set because of the effect of nonlinear conditional heteroscedasticity, and ANFIS in fact cannot overcome this problem resulted in a trained model that is not the optimal one. ANFISNCH model employing segmented adaptive support vector regression (SASVR) learning algorithm to adjust between ANFIS output and nonlinear conditional heteroscedasticity can best fit the model and greatly reduces the occurrence of extreme outliers in the predicted outputs from ANFISCH.
Ambient intelligence: visualising the future
Authors: Emile Aarts
Venue: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies (2005)

Ambient Intelligence systems are aimed at making user-system interaction and content consumption a truly positive experience. The endless search for nifty information visualisation mechanism to squeeze yet one more piece of information onto a visual display is surpassed by the challenge to embed interactive displays into our environments that bring true user experience. Examples of experiences supported by immersiveness, social intelligence and freedom have been investigated in the Philips HomeLab. HomeLab offers an unique scientific environment for evaluating the feasibility and usability of technologies that are used in the realisation of Ambient Intelligent scenarios. Equipped with an extensive observation infrastructure of 34 cameras and microphones, the HomeLab has enabled behavioural researchers to study the effect of innovative technologies on the user's acceptance for Ambient Intelligence. In the presentation we discuss recent developments resulting from our work in HomeLab with an emphasis on the relation between (information) visualization and experiences.
Formalization of input and output in modern operating systems: the hadley model
Authors: Matthew Burnett Gerber
Venue:  (2005)

We present the Hadley model, a formal descriptive model of input and output for modern computer operating systems. Our model is intentionally inspired by the Open Systems Interconnection model of networking; I/O as a process is defined as a set of translations between a set of computer-sensible forms, or layers, of information. To illustrate an initial application domain, we discuss the utility of the Hadley model and a potential associated I/O system as a tool for digital forensic investigators. To illustrate practical uses of the Hadley model we present the Hadley Specification Language, an essentially functional language designed to allow the translations that comprise I/O to be written in a concise format allowing for relatively easy verifiability. To further illustrate the utility of the language we present a read/write Microsoft DOS FAT12 and read-only Linux ext2 file system specification written in the new format. We prove the correctness of the read-only side of these descriptions. We present test results from operation of our HSL-driven system both in user mode on stored disk images and as part of a Linux kernel module allowing file systems to be read. We conclude by discussing future directions for the research.
Modeling word burstiness using the Dirichlet distribution
Authors: Rasmus E. Madsen, David Kauchak, Charles Elkan
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

Multinomial distributions are often used to model text documents. However, they do not capture well the phenomenon that words in a document tend to appear in bursts: if a word appears once, it is more likely to appear again. In this paper, we propose the Dirichlet compound multinomial model (DCM) as an alternative to the multinomial. The DCM model has one additional degree of freedom, which allows it to capture burstiness. We show experimentally that the DCM is substantially better than the multinomial at modeling text data, measured by perplexity. We also show using three standard document collections that the DCM leads to better classification than the multinomial model. DCM performance is comparable to that obtained with multiple heuristic changes to the multinomial model.
SEWSIP..Semantic based Web services Integration in P2P
Authors: LI Juanzi, XU Bin, YANG Wenjun, CHEN Dewei, ZHANG Po, WANG Kehong
Venue: Proceedings of the IEEE International Workshop (2005)

Semantic based Web services integration aims to add valuable semantic information in Web services Description and to implement the semantic based Web services discovery and integration. This paper puts forward a semantic based Web service integration framework in P2P-SEWSIP. SEWSIP can collect Web services in distributed web environment, lift the WSDL files into OWL-S by the use of XML schema in WSDL and domain ontology, and then deploy them in P2P. It also can provide service discovery, evaluation and composition based on semantic information in OWL-S.
Designing a Binary Neural Network Co-processor
Authors: Michael Freeman, Jim Austin
Venue: Proceedings of the 8th Euromicro Conference on Digital System Design (2005)

A Correlation Matrix Memory (CMM) is a form of binary neural network, that can be used for high-speed approximate search and match operations on large unstructured datasets. Typically, the processing requirements for a CMM do not map efficiently onto a modern processor based system. Therefore, an application specific co-processor is normally used to improve performance. This paper outlines two possible FPGA based co-processors for executing core CMM operations based upon a compact bit vector (CBV) data format. This representation significantly increases a system¿s storage capacity, but reduces processing performance.
Finite time bounds for sampling based fitted value iteration
Authors: Csaba Szepesvári, Rémi Munos
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

In this paper we consider sampling based fitted value iteration for discounted, large (possibly infinite) state space, finite action Markovian Decision Problems where only a generative model of the transition probabilities and rewards is available. At each step the image of the current estimate of the optimal value function under a Monte-Carlo approximation to the Bellman-operator is projected onto some function space. PAC-style bounds on the weighted Lp-norm approximation error are obtained as a function of the covering number and the approximation power of the function space, the iteration number and the sample size.
FS3: A Random Walk Based Free-Form Spatial Scan Statistic for Anomalous Window Detection
Authors: Vandana P. Janeja, Vijayalakshmi Atluri
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

Often, it is required to identify anomalous windows over a spatial region that reflect unusual rate of occurrence of a specific event of interest. A spatial scan statistic essentially considers a scan window, and identifies anomalous windows by moving the scan window in the region. While spatial scan statistic has been successful, earlier proposals suffer from two limitations: (i) They resrict the scan window to be of a regular shape (e.g., circle, rectangle, cylinder). However, the region of anomaly, in general, is not necessarily of a regular shape. (ii) They take into account autocorrelation among spatial data, but not spatial heterogeneity. As a result, they often result in inaccurate anomalous windows. To address these limitations, we propose a random walk based Free-Form Spatial Scan Statistic (FS³). Application of FS³ on real datasets has shown that it can identify more refined anomalous windows with better likelihood ratio of it being an anomaly, than those identified by earlier spatial scan statistic approaches.
GENIO: an ambient intelligence application in home automation and entertainment environment
Authors: Alfonso Gárate, Nati Herrasti, Antonio López
Venue: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies (2005)

As one of the main aims of "Ambient Intelligence" is natural human interaction with the environment and one the most suitable is the home environment. Fagor has been working several years to develop a power-line network where all its household appliances, security sensors and actuators, heating systems and antiintrusion systems are connected and managed by a central controller named Maior-Domo. As a result of GENIO project, the user can dialog with his home and asks the services and functionalities he wants by talking as he was talking to a friend. The controller Maior-Domo has a human representation that the user can see and can interact with. When the user talks the Maior-Domo extracts the different commands from those vocal orders and controls the home devices. These orders are not specific commands that the user has to learn but natural speaking language without any need of learning. In the same way, any event or information from any device of the network is transmitted to the user by voice. In order to achieve a demonstrator of this Ambient Intelligence application, a real kitchen and sitting room have been built where the users can command the home talking naturally (in Spanish). Possible actions are: reading e-mails, programming the washing machine, checking the goods in the fridge, creating the shopping list, doing shopping with a PDA in the supermarket, activating the dishwasher, being guided on how to prepare a recipe for the oven checking if there are the needed goods to do it, listening some music stored at home, watching some photos, watching some selected video and so on. Every user has a wireless microphone in his/her shirt's pocket. This microphone captures his/her voice and all the sounds around him/her and sends them to a developed board which filters the voice frequency range from other sounds. From here the voice recognition system "understands" the pronounced sentence and process it. A quite extended number of sentences, called grammar, make up the possible dialogue between the person and the whole system. The user can address the whole system in different ways using a lot of expressions, talking naturally and spontaneously and dialoguing to the home. The defined grammar is so extended that almost the total speaker independence has been achieved.
How to use crowding selection in Grammar-based Classifier System
Authors: Olgierd Unold, Lukasz Cielecki
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

Grammar-based classifier system (GCS) is a new version of Learning Classifier Systems (LCS) in which classifiers are represented by context-free grammar in Chomsky Normal Form. GCS evolves one grammar during induction (the Michigan approach) what gives it an ability to find the proper set of rules very quickly. However it is quite sensitive to any variations of learning parameters. This paper investigates the role of crowding selection in GCS. To evaluate the performance of GCS depending on crowding factor and crowding subpopulation we used context-free language in the form of so-called toy language. The set of experiments was performed to obtain the answer for the raised question in the title.
Ontology-Based Actively Discovering Potential Demands of Service Object
Authors: Maogou Chen, Gengfeng Wu, Jie Yuan, Jinsu Ma
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

Service providers always passively respond to the demands from service objects in traditional information service model. The function and efficiency of service provider are strongly restricted by this kind of passive model. Therefore, we brought up a "Symmetrical and Active Service Model" (SASM) in reference [1]. This article, aiming at the key points of SASM, proposes a system of Ontology-Based Actively Discovering Potential Demands of service objects (OBADPD). In the OBADPD, service provider can determine service objects initiatively by obtaining the status variation; inferring and filtering potential demands of service objects based on some relevant Ontology. In order to describe the process of discovering potential demands of service object, the car life ontology, problem solving ontology and reasoning method in OBADPD are introduced. Finally, some interesting instances are given to show the process.
Let's agree to disagree
Authors: Shiva Nejati, Marsha Chechik
Venue: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering (2005)

Almost every kind of software development periodically needs to merge models. Perhaps they come from different stakeholders during the requirements analysis phase, or perhaps they are modifications of the same model done independently by several groups of people. Sometimes these models are consistent and can be merged. Sometimes they are not, and negotiation between the stakeholders is needed in order to resolve inconsistencies. While various methods support merging, we need formal approaches that help stakeholders negotiate. We present a formal framework for merging and conflict resolution. It facilitates automatic merging of consistent models, enables users to visualize and explore potential disagreements and identify their priorities, and suggests ways to resolve the priority items.
Relating reinforcement learning performance to classification performance
Authors: John Langford, Bianca Zadrozny
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

We prove a quantitative connection between the expected sum of rewards of a policy and binary classification performance on created subproblems. This connection holds without any unobservable assumptions (no assumption of independence, small mixing time, fully observable states, or even hidden states) and the resulting statement is independent of the number of states or actions. The statement is critically dependent on the size of the rewards and prediction performance of the created classifiers.We also provide some general guidelines for obtaining good classification performance on the created subproblems. In particular, we discuss possible methods for generating training examples for a classifier learning algorithm.
Sub-Optimal Routing in Unreliable Packet-Switched Computer Communication Network
Authors: Adam Grzech
Venue: Proceedings of the 18th International Conference on Systems Engineering (2005)

The paper is devoted to introduce and describe an approach leading to sub-optimal traffic routing in unreliable packet-switched computer network. It is assumed that average packet delay in unreliable network may be estimated based on average packet delays obtained both for the reliable and the unreliable networks; it is approximated by linear function of both considered delays. It is also assumed that optimal routing in network, when failure of particular channel occurs may be replaced by re-routing performed only in some separate part of the network containing the channel with failure.
Architecture-Based Autonomous Repair Management: An Application to J2EE Clusters
Authors: Sara Bouchenak, Fabienne Boyer, Sacha Krakowiak, Daniel Hagimont, Adrian Mos, Stefani Jean-Bernard, Noel de Palma, Vivien Quema
Venue: Proceedings of the 24th IEEE Symposium on Reliable Distributed Systems (2005)

This paper presents a component-based architecture for autonomous repair management in distributed systems, and a prototype implementation of this architecture, called JADE, which provides repair management for J2EE application server clusters. The JADE architecture features three major elements, which we believe to be of wide relevance for the construction of autonomic distributed systems: (1) a dynamically configurable, component-based structure that exploits the reflective features of the FRACTAL component model; (2) an explicit and configurable feedback control loop structure, that manifests the relationship between the managed system and repair management functions; (3) an original replication structure for the management subsystem itself, which makes it fault-tolerant and self-healing.
Dynamic Tree Reconstruction with Application to Timing-Constrained Congestion-Driven Global Routing
Authors: Jin-Tai Yan, Chia-Fang Lee, Yen-Hsiang Chen
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

In this paper, based on timing-constrained Steiner-point location flexibility in any Y-type wire, a dynamic SA-based timing-constrained flexibility-driven SRT (DSTF_SRT) approach with the congestion weighs is firstly proposed to obtain a better timing-constrained flexibility-driven SRT by reassigning the feasible locations of the Steiner points in a SRT. Furthermore, the concept of dynamic tree reconstruction is applied to timing-constrained congestion-driven global routing. The experimental results show that our proposed TCGR_DTR algorithm can obtain a better timing-constrained congestion-driven global routing result than the HBA+TRR[8] and TCGR[9] algorithm for the tested benchmark circuits.