ppxscal/embedding_network huggingface dataset:
Document image characterization using a multiresolution analysis of the texture: application to old documents
Authors: Nicholas Journet, Jean-Yves Ramel, R&#x00e9;my Mullot, V&#x00e9;ronique Eglin
Venue: International Journal on Document Analysis and Recognition (2008)

In this article, we propose a method of characterization of images of old documents based on a texture approach. This characterization is carried out with the help of a multi-resolution study of the textures contained in the images of the document. Thus, by extracting five features linked to the frequencies and to the orientations in the different areas of a page, it is possible to extract and compare elements of high semantic level without expressing any hypothesis about the physical or logical structure of the analyzed documents. Experimentation based on segmentation, data analysis and document image retrieval tools demonstrate the performance of our propositions and the advances that they represent in terms of characterization of content of a deeply heterogeneous corpus.
On an apparent limit to verb idiosyncrasy, given a mapping between argument realization and polysemy (or argument optionality)
Authors: Don Perlis, Tim Oates
Venue:  (2007)

Full-scale natural language processing systems require lots of information on thousands of words. This is especially true for systems handling the meanings of words and phrases, and it seems especially true for the verbs of a language: at first glance at least, and when viewed as if they were argument-taking functions, verbs seem to have highly individual requirements&mdash;along at least two dimensions. (1) They vary in the range of arguments they take (further complicated by polysemy, i.e. the proliferation of their senses). And to a significant extent (2) they vary in the way in winch those arguments are realized in syntax. Since arbitrary information must be stored anyway&mdash;such as the particular concept pairing with the sound and/or spelling of a word&mdash;it seems reasonable to expect to store other potentially idiosyncratic information, including what might be needed for polysemy and argument realization. But once the meanings of words are stored, it isn't completely clear how much else really needs to be stored, in principle. With a significant degree of patterning in polysemy, and in argument realization, real speakers extrapolate from known senses and realizations. To fully model the processing of natural language, there must be at least some automatic production, and/or verification, of polysemy and argument realization, from the semantics. Since there are two phenomena here (polysemy and argument realization), the interaction between them could be crucial; and indeed particular instances of this interaction appear again and again in theoretical studies of syntax and meaning. Yet the real extent of the interaction has not itself been properly investigated. To do so, we supply, for the argument-taking configurations of 3000 English verbs, the typical kind of semantic: specification&mdash;on the roles of their arguments&mdash;but do a kind of high-level analysis of the resulting patterns. The results suggest a rule of co-occurrences: divergences in argument realization are in fact rigorously accompanied by divergences in polysemy or argument optionality. We argue that this implies the existence of highly productive mechanisms for polysemy and argument realization, thus setting some crucial groundwork for their eventual production by automated means.
Deliberative discourse and reasoning from generic argument structures
Authors: John L. Yearwood, Andrew Stranieri
Venue: AI Society (2008)

In this article a dialectical model for practical reasoning within a community, based on the Generic/Actual Argument Model (GAAM) is advanced and its application to deliberative dialogue discussed. The GAAM, offers a dynamic template for structuring knowledge within a domain of discourse that is connected to and regulated by a community. The paper demonstrates how the community accepted generic argument structure acts to normatively influence both admissible reasoning and the progression of dialectical reasoning between participants. It is further demonstrated that these types of deliberation dialogues supported by the GAAM comply with criteria for normative principles for deliberation, specifically, Alexy&#x2019;s rules for discourse ethics and Hitchcock&#x2019;s Principles of Rational Mutual Inquiry. The connection of reasoning to the community in a documented and transparent structure assists in providing best justified reasons, principles of deliberation and ethical discourse which are important advantages for reasoning communities.
Goal generation with relevant and trusted beliefs
Authors: Célia da Costa Pereira, Andrea G. B. Tettamanzi
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

A rational agent adopts (or changes) its goals when new information (beliefs) becomes available or its desires (e.g., tasks it is supposed to carry out) change. In conventional approaches to goal generation in which a goal is considered as a "particular" desire, a goal is adopted if and only if all conditions leading to its generation are satisfied. It is then supposed that all beliefs are equally relevant and their sources completely trusted. However, that is not a realistic setting. In fact, depending on the agent's trust in the source of a piece of information, an agent may decide how strongly it takes into consideration such piece of information in goal generation. On the other hand, not all beliefs are equally relevant to the adoption of a given goal, and a given belief may not be equally relevant to the adoption of different goals. We propose an approach which takes into account both the relevance of beliefs and the trust degree of the source from which the corresponding piece of information comes, in desire/goal generation. Two algorithms for updating the mental state of an agent in this new setting and three ways for comparing the resulting fuzzy set of desires have been given. Finally, two fundamental postulates any rational goal election function should obey have been stated.
Efficient Key Management for Three Dimensional Node Deployment in WSN
Authors: Kyeong-Hyo Lee, Byeong-Kyun Oh, Seok-Kyun Han, Sang-Gug Lee
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

A low-power sensor node in WSN requires minimum consumption of energy. It is essential to establish key to reduce the effect when the sensor node is revealed. This paper propose the protocol of pairwise key establishment between sensor node. The proposed method increases the availability by clustering the network in three dimensional, which has smaller number of path and better energy efficiency than the plane allocation. This paper discusses the key management for secure communication between sensor nodes after sensor allocation. We propose the protocol of pairwise key Establishment scheme using Bivariate Polynomial based on cluster in order to safety against attack by revealing of node. The proposed method guarantee the availability by clustering the network in three dimensional, which has smaller number of path and better energy efficiency.
Contrastive divergence in gaussian diffusions
Authors: Javier R. Movellan
Venue: Neural Computation (2008)

This letter presents an analysis of the contrastive divergence (CD) learning algorithm when applied to continuous-time linear stochastic neural networks. For this case, powerful techniques exist that allow a detailed analysis of the behavior of CD. The analysis shows that CD converges to maximum likelihood solutions only when the network structure is such that it can match the first moments of the desired distribution. Otherwise, CD can converge to solutions arbitrarily different from the log-likelihood solutions, or they can even diverge. This result suggests the need to improve our theoretical understanding of the conditions under which CD is expected to be well behaved and the conditions under which it may fail. In, addition the results point to practical ideas on how to improve the performance of CD.
A Near-Tight Bound for the Online Steiner Tree Problem in Graphs of Bounded Asymmetry
Authors: Spyros Angelopoulos
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

The edge asymmetry of a directed, edge-weighted graph is defined as the maximum ratio of the weight of antiparallel edges in the graph, and can be used as a measure of the heterogeneity of links in a data communication network. In this paper we provide a near-tight upper bound on the competitive ratio of the Online Steiner Tree problem in graphs of bounded edge asymmetry ¿. This problem has applications in efficient multicasting over networks with non-symmetric links. We show an improved upper bound of $O \left (\min \left \{ \max \left \{ \alpha \frac{\log k}{\log \alpha}, \alpha \frac{\log k}{\log \log k} \right \} ,k \right \} \right )$ on the competitive ratio of a simple greedy algorithm, for any request sequence of k terminals. The result almost matches the lower bound of $\Omega \left (\min \left \{ \max \left \{ \alpha \frac{\log k}{\log \alpha}, \alpha \frac{\log k}{\log \log k} \right \}, k^{1-\epsilon} \right \} \right )$ (where ¿ is an arbitrarily small constant) due to Faloutsos et al. [8] and Angelopoulos [2].
CBP: A New Efficient Method for Mining Multilevel and Generalized Frequent Itemsets
Authors: Yu Xing Mao, Bai Shi
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

The taxonomy(is-a hierarchy) data exists widely in retail, geography, biology and financial area, so mining the multilevel and generalized association rules is one of the most important research task in data mining. Unlike the traditional algorithm, which is based on Apriori method, we propose a new CBP (correlation based partition) based method, to mine the multilevel and generalized frequent itemsets. This method uses the item's correlation as measurement to partition the transaction database from top to bottom. It can shorten the time of mining multilevel and generalized frequent itemsets by reducing the scanning scope of the transaction database. The experiments on the real-life financial transaction database show that the CBP based algorithms outperform the well-known Apriori based algorithms.
Coupled electromagnetic, thermal and stress analysis of large power electrical transformers
Authors: Daniela Cârstea, Alexandru Adrian Cârstea, Ion Cârstea
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

Investigating the electromagnetic, thermal and stress fields inside an electrical transformer of large power delivers knowledge for predicting its performance. The mathematical models for the three processes are coupled and allow an accurate analysis on windings level as well as the prediction of the overall performance of the transformer. In this work we survey our research on a model described by a set of equations for the three fields. The interconnection of the three fields is given on the one hand implicitly by the temperature dependence on the material properties, on the other hand explicitly by the heat sources in the thermal model controlled by the Joule's effect in the electromagnetic system. As target example we use a power transformer, important equipment used in transmission and distribution of the energy. We present a numerical magneto-thermal-stress model for an encapsulated three-phase transformer. The model is based on the coupled approach and involves a stress analysis coupled with the computation of the power losses in the coils determined from the electromagnetic field and heat transfer analysis. The numerical models for the analysis of the coupled fields are based on the finite element method for axisymmetric fields.
Coal and Gas Outburst Prediction Combining a Neural Network with the Dempster-Shafter Evidence
Authors: Yanzi Miao, Jianwei Zhang, Houxiang Zhang, Xiaoping Ma, Zhongxiang Zhao
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

A novel prediction method combing a neural network with the D-S evidence theory for coal and gas outbursts is put forward in this paper. We take advantage of the fact that the non-linear input-output mapping function of the neural network can handle the non-linear parameters from coal and gas outburst monitor systems. And the output of the neural network is taken as the basic probability of the assignment function of the D-S evidence theory, which resolves the main problem of establishing the BPAF for the D-S evidence theory. The results from our experiments show that it is feasible and effective to combine the neural network with the D-S evidence theory for deciding on predictions. And using this method, we can make a more certain and credible prediction decision than witheach independent method.
Real-Time Collection of Electromagnetic Field Measurements Using a Metropolitan Wireless Mesh Network
Authors: Nikolaos Petroulakis, Vasilios A. Siris
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

We present a system for real-time collection of Electromagnetic Field (EMF) measurements. The two innovative features of the system that differentiate it from other similar monitoring systems are the use of a low-cost EMF measurement device and the collection and access of measurements through a metropolitan wireless mesh network. The low-cost EMF measurement device is connected to a mini-ITX based PC, and both are located in a water-proof enclosure. The EMF monitoring node is connected to a metropolitan wireless mesh network, which we have deployed in the city of Heraklion, Crete. A set of software module are responsible for collecting, processing, and presenting the EMF measurements in the form of graphs that are accessible from a web browser. The software modules support per-band, per-operator, and time-series monitoring, in addition to on-demand monitoring of a specific frequency range and time interval.
The Art of Granular Computing
Authors: Yiyu Yao
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

The current research in granular computing is dominated by set-theoretic models such as rough sets and fuzzy sets. By recasting the existing studies in a wider context, we propose a unified framework of granular computing. The new framework extends results obtained in the set-theoretic setting and extracts high-level common principles from a wide range of scientific disciplines. The art of granular computing for problem solving emerges from the resulting common philosophy, methodology and information processing paradigm. Granular computing stresses not only the need for rigor, structure, conciseness and clarity, but also the importance of conscious effects and wisdom in using powerful strategies and heuristics in stating and solving problems.
The Making of Colossus
Authors: Allen W. M. Coombs
Venue: IEEE Annals of the History of Computing (1983)

The article describes the techniques that evolved for the design and manufacture of the Colossus machines and their auxiliaries, invented for the purpose of code breaking during World War II and installed at Bletchley Park.
Classification of packed executables for accurate computer virus detection
Authors: Roberto Perdisci, Andrea Lanzi, Wenke Lee
Venue: Pattern Recognition Letters (2008)

Executable packing is the most common technique used by computer virus writers to obfuscate malicious code and evade detection by anti-virus software. Universal unpackers have been proposed that can detect and extract encrypted code from packed executables, therefore potentially revealing hidden viruses that can then be detected by traditional signature-based anti-virus software. However, universal unpackers are computationally expensive and scanning large collections of executables looking for virus infections may take several hours or even days. In this paper we apply pattern recognition techniques for fast detection of packed executables. The objective is to efficiently and accurately distinguish between packed and non-packed executables, so that only executables detected as packed will be sent to an universal unpacker, thus saving a significant amount of processing time. We show that our system achieves very high detection accuracy of packed executables with a low average processing time.
A Hybrid Particle Swarm Optimization for Feed-Forward Neural Network Training
Authors: Ben Niu, Li Li
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

This paper employs a hybrid particle swarm optimization using optimal foraging theory (PSOOFT) for multilayer feed-forward neural network (MFNN) training. Three benchmark classification problems: Iris, Newthyroid and Glass are conducted to measure the performance of PSOOFT based MFNN. The simulation results are also compared with obtained using back Propagation (BP), genetic algorithm (GA) and standard PSO (SPSO) approaches to demonstrate the effectiveness and efficiency of PSOOFT.
Bridging the Gap Between Simulation and Reality in Urban Search and Rescue
Authors: Stefano Carpin, Mike Lewis, Jijun Wang, Steve Balakirsky, Chris Scrapper
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

Research efforts in urban search and rescue grew tremendously in recent years. In this paper we illustrate a simulation software that aims to be the meeting point between the communities of researchers involved in robotics and multi-agent systems. The proposed system allows the realistic modeling of robots, sensors and actuators, as well as complex unstructured dynamic environments. Multiple heterogeneous agents can be concurrently spawned inside the environment. We explain how different sensors and actuators have been added to the system and show how a seamless migration of code between real and simulated robots is possible. Quantitative results supporting the validation of simulation accuracy are also presented.
Sketch-based Interfaces: Sketching contours
Authors: Johannes Zimmermann, Andrew Nealen, Marc Alexa
Venue: Computers and Graphics (2008)

We introduce an over-sketching interface for feature-preserving surface mesh editing. The user sketches a stroke that is the suggested position of part of a silhouette of the displayed surface. The system then segments all image-space silhouettes of the projected surface, identifies among all silhouette segments the best matching part, derives vertices in the surface mesh corresponding to the silhouette part, selects a sub-region of the mesh to be modified, and feeds appropriately modified vertex positions together with the sub-mesh into a mesh deformation tool. The overall algorithm has been designed to enable interactive modification of the surface-yielding a surface editing system that comes close to the experience of sketching 3D models on paper.
The FOREVER service for fault/intrusion removal
Authors: Paulo Sousa, Alysson Neves Bessani, Rafael R. Obelheiro
Venue: Proceedings of the 2nd workshop on Recent advances on intrusiton-tolerant systems (2008)

This paper introduces FOREVER, a novel service that can be used to enhance the resilience of replicated systems, namely those exposed to malicious attacks. The main objective of FOREVER is to remove faults and intrusions that may happen during system execution, and such removal is done by combining both evolution and recovery techniques. The paper presents (i.) the challenges that systems exposed to malicious attacks need to address, and (ii.) how FOREVER can be used to tackle these challenges.
Product Cubic Phase Function Algorithm for Estimating the Instantaneous Frequency Rate of Multicomponent Two-Dimensional Chirp Signals
Authors: Kunlei Zhang, Shuxun Wang, Fan Cao
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

The problem of concern here is instantaneous frequency rate (IFR) estimation of multicomponent two-dimensional (2-D) chirp signals. First, the 2-D cubic phase function (CPF) is defined. However, when the 2-D CPF is used to dealing with multicomponent 2-D chirp signals, the spurious peaks arise due to the existing of cross term. Then the definition of 2-D product cubic phase function (PCPF) is given by multiplying the corresponding 2-D CPF slices. Using 2-D PCPF, the spurious peaks are suppressed and IFR of 2-D chirp signals under low SNR can be estimated accurately. Simulations are provided to verify the theoretical claims.
Improved BDD Algorithms for the Simulation of Quantum Circuits
Authors: Vasilis Samoladas
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

In this paper we develop novel algorithms for the simulation of quantum circuits on classical computers. The most efficient techniques previously studied, represent both quantum state vectors and quantum operator matrices as Multi-Terminal Binary Decision Diagrams (MTBDDS). This paper shows how to avoid representing quantum operators as matrices. Instead, we introduce a class of quantum operators that can be represented more compactly using a symbolic, BDD-based representation. We propose algorithms that apply operators on quantum states, using the symbolic representation. Our algorithms are shown to have superior performance over previous techniques, both asymptotically and experimentally.
Relative capacity: Retaining knowledge outside a firm's boundaries
Authors: Ulrich Lichtenthaler
Venue: Journal of Engineering and Technology Management (2008)

Besides internalizing external knowledge, companies may maintain knowledge in interfirm relationships over time. Thus, interorganizational relations may be regarded as an extended knowledge base to which a firm has privileged access. We merge research into knowledge management, absorptive capacity, learning, and dynamic capabilities to analyze knowledge retention outside a firm's boundaries. Prior research into knowledge management has focused on internally storing knowledge, whereas research into knowledge transactions has primarily studied the internalization of external knowledge. The need to dynamically manage knowledge in interfirm relations over time - without necessarily internalizing this knowledge - has been relatively neglected. Therefore, we develop the foundations of the dynamic capability-based concept of relative capacity as a complement to absorptive capacity and transformative capacity in external knowledge retention. Relative capacity contributes to explaining interfirm differences in knowledge strategies, alliance strategies, organizational boundaries, open innovation, and performance. To guide further research, propositions are advanced regarding the antecedents and consequences of relative capacity.