ppxscal/embedding_network huggingface dataset:
Reordering of Location Identifiers for Indexing an RFID Tag Object Database
Authors: Sungwoo Ahn, Bonghee Hong
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

The query performance for tracing tags depends upon the distribution of tag trajectories in the data space. We examine a more efficient representation of tag trajectories by means of ordering the set of domain values. Our analysis shows that the order of Location IDentifiers (LIDs) can give a great impact on the efficiency of query processing. To find out the optimal ordering of LIDs, we propose a new LID proximity function to rearrange an arbitrary order of LIDs. This function enables logically adjacent tag trajectories, which are frequently accessed together, to be stored in close proximity on the disk. To determine the optimal sequence of LIDs in the domain, we also propose a reordering scheme of LIDs. The experimental results show that the proposed reordering scheme achieves better query processing than the previous methods of assigning LIDs.
Approximate Solution of a PEPA Model of a Key Distribution Centre
Authors: Yishi Zhao, Nigel Thomas
Venue: Proceedings of the SPEC international workshop on Performance Evaluation: Metrics, Models and Benchmarks (2008)

In this paper we explore the trade-off between security and performance in considering a model of a key distribution centre. The model is specified using the Markovian process algebra PEPA. The basic model suffers from the commonly encountered state space explosion problem, and so we apply some model reduction techniques and approximation to give a form of the model which is more scalable. The system is analysed numerically and results derived from the approximation are compared with simulation.
A Second Course in Formal Languages and Automata Theory, 1 edition
Authors: Jeffrey Shallit
Venue:  (2008)

Intended for graduate students and advanced undergraduates in computer science, A Second Course in Formal Languages and Automata Theory treats topics in the theory of computation not usually covered in a first course. After a review of basic concepts, the book covers combinatorics on words, regular languages, context-free languages, parsing and recognition, Turing machines, and other language classes. Many topics often absent from other textbooks, such as repetitions in words, state complexity, the interchange lemma, 2DPDAs, and the incompressibility method, are covered here. The author places particular emphasis on the resources needed to represent certain languages. The book also includes a diverse collection of more than 200 exercises, suggestions for term projects, and research problems that remain open.
What to Learn from Different Standards and Measurement Approaches? Is a Pragmatic Integrative Approach Possible?
Authors: Fabio Bella, Horst Degen-Hientz
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

Several measurement approaches such as Balanced Score Cards (BSC), Six Sigma, or Goal Question Metrics (GQM), can be applied to set up and embedd measurement programs within the scope of software projects. Different approaches may highlight different aspects of the measurement process or address different organizational levels. They may also show complementary aspects and provide a maximum of benefit when jointly applied. Often different approaches are applied by different groups within one same organization and effort has to be spent to integrate different measurement initiatives. To maximize the information gain and minimize the effort to be spent in measurement-related activities, informed decisions have to be made and the right approaches must be chosen when setting up a measurement program. The aim of this workshop is to present single measurement approaches currently available, share experience gathered from their application, and sketch a map to assist preliminary decision making when defining measurement programs.
The Evaluation and Design Methodology for Real Time Systems
Authors: Egidijus Kazanavičius
Venue: Informatica (2004)

Petri net variants are widely used as a real time systems modeling technique. Recently, UML activity diagrams have been used for the same purpose, even though the syntax and semantics of activity diagrams has not been yet fully worked out. Nevertheless, activity diagrams seem very similar to Petri net semantics. UML, being the industry standard as a common object oriented modeling language needs a well-defined semantic base for its notation. Formalization of the graphical notation enables automated processing and analysis tasks. Petri nets can provide a formal semantic framework for the UML notations plus the behavioral modeling/analysis strength needed to system designers. This paper describes the methodology for creating the model of the RT application that would allow testing the correctness of the algorithm and the fulfillment of the time constraints at the design stage using UML and Petri Nets.
Recent Advances in the Neocognitron
Authors: Kunihiko Fukushima
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

The neocognitron is a hierarchical multilayered neural network capable of robust visual pattern recognition. This paper discusses recent advances in the neocognitron, showing several types of neocognitron, to which various improvements and modifications have been made.
A Forward Constrained Selection Algorithm for Probabilistic Neural Network
Authors: Ning Zong, Xia Hong
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

A new probabilistic neural network (PNN) learning algorithm based on forward constrained selection (PNN-FCS) is proposed. An incremental learning scheme is adopted such that at each step, new neurons, one for each class, are selected from the training samples and the weights of the neurons are estimated so as to minimize the overall misclassification error rate. In this manner, only the most significant training samples are used as the neurons. It is shown by simulation that the resultant networks of PNN-FCS have good classification performance compared to other types of classifiers, but much smaller model sizes than conventional PNN.
Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models
Authors: Byron M. Yu, John P. Cunningham, Krishna V. Shenoy, Maneesh Sahani
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

To date, the neural decoding of time-evolving physical state --- for example, the path of a foraging rat or arm movements --- has been largely carried out using linear trajectory models, primarily due to their computational efficiency. The possibility of better capturing the statistics of the movements using nonlinear trajectory models, thereby yielding more accurate decoded trajectories, is enticing. However, nonlinear decoding usually carries a higher computational cost, which is an important consideration in real-time settings. In this paper, we present techniques for nonlinear decoding employing modal Gaussian approximations, expectatation propagation, and Gaussian quadrature. We compare their decoding accuracy versus computation time tradeoffs based on high-dimensional simulated neural spike counts.
Neural-Network-Based Switching Control for DC Motors System with LFR
Authors: Jianhua Wu, Shuying Zhao, Lihong He, Lanfeng Chen, Xinhe Xu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

The Loss-Free resistor (LFR) is applied to DC motor speed control system. A compensation Control algorithm based on LFR is proposed. The LFR is realized by means of switching network whose characteristics are nonlinear, thus, a neural network was designed and used. The switching on-off time can be instantaneously calculated by using the Neural-network-based algorithm proposed. The varies of the motor speed is realized by controlling the output of the LFR, the energy loss in the system is reduced compared with using a conventional power amplifier, and the dynamic characteristics of the system are also improved. The validation of the simulation results is proposed as well.
Algorithms for classification and prediction of protein structure and function
Authors: Jieun Jeong
Venue:  (2007)

The subject of this thesis is predicting the function of a protein. Many aspects of protein function are determined by its shape, or the structure. This thesis discusses methods for converting sets of local predictions concerning the structure of a protein chain to an overall prediction of the structure. One approach was to define a similarity function for chains of &ldquo;local predictions&rdquo; and to use this function to rank the prepositions that the input protein belongs to a particular fold from the most likely to the least likely. This is called fold classification. We show how to use information that is not local from the point of view of a protein chain, namely, which loops are closed, to improve the quality of classification. In the process, a weakness in the previous evaluation method was discovered and a better method proposed and tested. The second approach is to start with predictions of secondary structures, strands and helices, and a predictor of propensity of beta-strands to form pairs, and to obtain the overall prediction of the pairing of strands. We discuss global optimization problems that this task can pose, their hardness and approximation algorithms. We also test several algorithms on biological data and find improvement in respect to a previous method. Other aspects of protein function are determined by their place in the networks of cellular interactions. We study the cycles in the transcription regulatory network of Saccharomyces cerevisiae, we find the graph-theoretic properties of these cycles, and we characterize the place of these cycles in the regulatory mechanism of the cell in terms of hierarchy. We also establish which life conditions are associated with the cycles and we conjecture the reasons.
Resource constrained distributed constraint optimization using resource constraint free pseudo-tree
Authors: Toshihiro Matsui, Marius Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hirohsi Matsuo
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

The Distributed Constraint Optimization Problem (DCOP) is a fundamental formalism for multi-agent cooperation. A dedicated framework called Resource Constrained DCOP (RCDCOP) has recently been proposed. RCDCOP models objective functions and resource constraints separately. A resource constraint is an n-ary constraint that represents the limit on the number of resources of a given type available to agents. Previous research addressing RCDCOPs employs the Adopt algorithm, which is a basic solver for DCOPs. In this paper we propose another version of the Adopt algorithm for RCDCOP using a pseudo-tree that is generated ignoring resource constraints. The key ideas of our work are as follows: (i) The pseudo-tree is generated ignoring resource constraints. (ii) Virtual variables are introduced, representing the usage of resources. These virtual variables are used to share resources among sub-trees. These ideas are used to extend Adopt. The proposed method reduces the previous limitations in the construction of RCDCOP pseudo-trees. The efficiency of our technique depends on the class of problems being considered, and we describe the obtained experimental results.
The Electronic Road: Personalized Content Browsing
Authors: Manolis Wallace, Kostas Karpouzis, George Stamou, George Moschovitis, Stefanos Kollias, Christos Schizas
Venue: IEEE MultiMedia (2003)

Conventional search engines locate terms in queried documents without taking into account their actual semantic content. Search engines also retrieve multimedia documents that aren't necessarily related to each other by semantic continuity. An efficient content-browsing system based on semantic content analysis, user profiling, and adaptation could provide users with more effective content-browsing capabilities.
User-Assisted Management of Agent-Based Evolutionary Computation
Authors: Aleksander Byrski, Marek Kisiel-Dorohinicki
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

In the paper the need and general idea of user-assisted management of computational intelligence systems is discussed. First some methodological issues are presented with particular attention paid to agent-based approaches. These general considerations are supported by the case of evolutionary multi-agent system (EMAS) with immunological selection, applied to multi-modal function optimization subjected to a user-driven tuning procedure. Finally, preliminary experimental results considering the influence of selected parameters on the performance of the system are shown.
John R. Pasta, 1918-1981-An Unusual Path Toward Computer Science
Authors: Kent K. Curtis, N. C. Metropolis, William G. Rosen, Yoshio Shimamoto, James N. Snyder
Venue: IEEE Annals of the History of Computing (1983)

The following eloge of John R. Pasta should remind readers that he died before recording his recollections and interpretations of his personal experiences as a contributor to the early development of computing. Sadly, what he might-have told us of what he thought when he did it is now lost forever. We will never have his firsthand account to help us learn how to do great things ourselves. I hope potential authors of reminiscences, memoirs, and autobiographies will act now to avoid further losses.
Interruption, Resumption and Domain Switching in In-Vehicle Dialogue
Authors: Jessica Villing, Cecilia Holtelius, Staffan Larsson, Anders Lindström, Alexander Seward, Nina Åberg
Venue: Proceedings of the 6th international conference on Advances in Natural Language Processing (2008)

The use of dialogue systems in vehicles raises the problem of making sure that the dialogue does not distract the driver from the primary task of driving. Earlier studies have indicated that humans are very apt at adapting the dialogue to the traffic situation and the cognitive load of the driver. The goal of this paper is to investigate strategies for interrupting and resuming in, as well as changing topic domain of, spoken human-human in-vehicle dialogue. The results show a large variety of strategies being used, and indicate that the choice of resumption and domain-switching strategy depends partly on the topic domain being resumed, and partly on the role of the speaker (driver or passenger). These results will be used as a basis for the development of dialogue strategies for interruption, resumption and domain-switching in the DICO in-vehicle dialogue system.
A Trusted Approach to E-Commerce
Authors: Giannakis Antoniou, Lynn Batten, Udaya Parampalli
Venue: Proceedings of the 5th VLDB workshop on Secure Data Management (2008)

It has been well documented that lack of trust between commercial entities and purchasers can restrict the potential of e-commerce. This may be because the purchaser is required to provide sensitive information to the commercial entity or because the purchaser may be suspicious that after payment has been processed, the goods purchased will not arrive. The challenge for the researcher is to determine the e-commerce model which maximizes the trust relationship. In this paper, we introduce a measure of the trust based on the information distributed to the parties in the transaction and isolate the instances which maximize trust for the purchaser. This leads us to propose four new models for e-commerce which would improve consumer trust and therefore likely lead to an increase in on-line commerce. We demonstrate that no new technologies are needed in order to implement these new models.
The Architecture of a Capability-Based Microprocessor System
Authors: Paolo Corsini, Lanfranco Lopriore
Venue: IEEE Micro (1987)

By implementing a capability-oriented addressing scheme, tagged storage, and a single-level-store approach to memory management, and by providing hardware support for multitasking, this architecture reduces the semantic gap.
Two Step Relevance Feedback for Semantic Disambiguation in Image Retrieval
Authors: Daniel Heesch, Stefan Rüger
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

This paper presents a new approach to the problem of feature weighting for content based image retrieval. If a query image admits to multiple interpretations, user feedback on the set of returned images can be an effective tool to improve retrieval performance in subsequent rounds. For this to work, however, the first results set has to include representatives of the semantic facet of interest. We will argue that relevance feedback techniques that fix the distance metric for the first retrieval round are semantically biased and may fail to distil relevant semantic facets thus limiting the scope of relevance feedback. Our approach is based on the notion of the NN k of a query image, defined as the set of images that are nearest neighbours of the query under some instantiation of a parametrised distance metric. Different neighbours may be viewed as representing different meanings of the query. By associating each NN k with the parameters for which it was ranked closest to the query, the selection of relevant NN k by a user provides us with parameters for the second retrieval round. We evaluate this two step relevance feedback technique on two collections and compare it to an alternative relevance feedback method and to an oracle for which the optimal parameter values are known.
An Improved Particle Swarm Optimizer for Truss Structure Optimization
Authors: Lijuan Li, Zhibin Huang, Feng Liu
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

This paper presents an improved particle swarm optimizer (IPSO) for solving truss structure optimization problems. The algorithm is based on the particle swarm optimizer with passive congregation (PSOPC) and a harmony search (HS) scheme. It handles the problem-specified constraints using a `fly-back mechanism' method and the variables' constraints using the harmony search scheme. The IPSO is tested on a planar truss structure optimization problem and is compared with the PSO and the PSOPC algorithm respectively. The result shows that the IPSO method presented in this paper is able to accelerate the convergence rate effectively and has the fastest convergence rate among these three other algorithms.
Double Sides 2DPCA for Face Recognition
Authors: Chong Lu, Wanquan Liu, Xiaodong Liu, Senjian An
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Recently, many approaches of face recognition have been proposed due to its broad applications. The generalized low rank approximation of matrices(GLRAM) was proposed in [1], and a necessary condition for the solution of GLRAM was presented in [2]. In addition to all these developments, the Two-Dimensional Principal Component Analysis (2DPCA) model is proposed and proved to be an efficient approach for face recognition [5]. In this paper, we proposed Double Sides 2DPCA algorithm via investigating the 2DPCA algorithm and GLRAM algorithm, experiments showed that the Double Sides 2DPCA's performance is as good as 2DPCA's and GLRAM's. Furthermore, the computation cost of recognition is less than 2DPCA and the computation speed is faster than that for GLRAM. Further, we present a new constructive method for incrementally adding observation to the existing eigen-space model for Double Sides 2DPCA, called incremental doubleside 2DPCA. An explicit formula for such incremental learning is derived. In order to illustrate the effectiveness of the proposed approach, we performed some typical experiments.
A Web Portal for Regional Projection of Weather Forecast Using GRID Middleware
Authors: A. S. Cofiño, D. San-Martín, J. M. Gutiérrez
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Weather forecast is a complex multi-disciplinary problem which requires a cascade of different scientific tools, from differential equation solvers to high-dimensional statistical and data-mining algorithms. The demand for high-resolution predictions is continuously increasing due to the multiple applications in hydrology, agronomy, etc., which require regional meteorological inputs. To fill the gap between the coarse-resolution lattices used by global weather models and the regional needs of applications, a number of statistical downscaling techniques have been proposed. In this paper we describe a Web portal which integrates the necessary tools with Grid middleware allowing for distributed data access and computing. The portal is part of the ENSEMBLES EU-funded project and allows end users to interactively downscale weather predictions using a web browser. Both the architecture and the usage of the portal are described in this paper.
Certain, Generalized Decision, and Membership Distribution Reducts Versus Functional Dependencies in Incomplete Systems
Authors: Marzena Kryszkiewicz
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

An essential notion in the theory of Rough Sets is a reduct, which is a minimal set of conditional attributes that preserves a required classification feature, e.g. respective values of an original or modified decision attribute. Certain decision reducts, generalized decision reducts, and membership distribution reducts belong to basic types of Rough Sets reducts. In our paper, we prove that reducts of these types are sets of conditional attributes functionally determining respective modifications of a decision attribute both in complete and incomplete information systems. However, we also prove that, unlike in the case of complete systems, the reducts in incomplete systems are not guaranteed to be minimal sets of conditional attributes that functionally determine respective modifications of the decision attribute.
Designing Narratology-Based Educational Games with Non-players
Authors: Yavuz Inal, Turkan Karakus, Kursat Cagiltay
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

Challenges of designing an educational game cause an ongoing debate that while one side proposes ludology as the key for a computer game, other side proposes narratology as the most important part of game environment. Ludologic attributes of games have been preferred more than narrative ones. However, results of studies attempted to reveal importance of narrative structures and storytelling for computer games, especially for educational ones. In the present study, narratology including storytelling and narrative structures will be discussed in terms of narratology-based educational computer game design. 46 non-player preservice teachers at Department of Foreign Language Education participated to the study. Participants, as subject matter experts on teaching English Language, designed educational game prototypes. Those prototypes were analyzed and reported according to their narrative aspects.