ppxscal/embedding_network huggingface dataset:
Employing a Domain Specific Ontology to Perform Semantic Search
Authors: Maxime Morneau, Guy W. Mineau
Venue: Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning (2008)

Increasing the relevancy of Web search results has been a major concern in research over the last years. Boolean search, metadata, natural language based processing and various other techniques have been applied to improve the quality of search results sent to a user. Ontology-based methods were proposed to refine the information extraction process but they have not yet achieved wide adoption by search engines. This is mainly due to the fact that the ontology building process is time consuming. An all inclusive ontology for the entire World Wide Web might be difficult if not impossible to construct, but a specific domain ontology can be automatically built using statistical and machine learning techniques, as done with our tool: SeseiOnto. In this paper, we describe how we adapted the SeseiOnto software to perform Web search on the Wikipedia page on climate change. SeseiOnto, by using conceptual graphs to represent natural language and an ontology to extract links between concepts, manages to properly answer natural language queries about climate change. Our tests show that SeseiOnto has the potential to be used in domain specific Web search as well as in corporate intranets.
Neuro-electrophysiological Argument on Energy Coding
Authors: Rubin Wang, Zhikang Zhang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

According to analysis of both neuro-electrophysiological experimental data and the biophysical properties of neurons, in early research paper we proposed a new biophysical model that reflects the property of energy coding in neuronal activity. On the based of the above research work, in this paper the proposed biophysical model can reproduce the membrane potentials and the depolarizing membrane current by means of neuro-electrophysiological experimental data. Combination with our previous research results, the proposed biophysical model is demonstrated again to be more effective compared with known biophysical models of neurons.
Introduction to Constructive and Optimization Aspects of SONN-3
Authors: Adrian Horzyk
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

The paper introduces new valuable improvements of performance, a construction and a topology optimization of the Self-Optimizing Neural Networks (SONNs). In contrast to the previous version (SONN-2), the described SONN-3 integrates the very effective solutions used in the SONN-2 with the very effective ADFA algorithms for an automatic conversion of real inputs into binary inputs. The SONN-3 is a fully constructive ontogenic neural network classificator based on a sophisticated training data analysis that quickly estimates values of individual real, integer or binary input features. This method carries out all computation fully automatically from a data analysis and a data input dimension reduction to a computation of a neural network topology and its weight parameters. Moreover, the SONN-3 computational cost is equal O(n log 2 n), where n is a sum of a data quantity, a data input dimension and a data output dimension. The results of the SONN-3 construction and optimization are illustrated and compared by means of some examples.
Evaluation of a Novel Load-Balancing Algorithm with Variable Granularity
Authors: Yi Dai, Lei Cao
Venue: Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing (2008)

In this paper, we propose a Uniform Fine-grain Frame Spreading (UFFS-k, where k is the aggregate factor) algorithm to guarantee packet ordering in load-balanced switches by assigning k cells of the same flow to the fixed k successive intermediate inputs. The UFFS-k algorithm first guarantees packet ordering at input linecards without any computation and communication overhead. As the simulation results demonstrate, UFFS-k offers improved delay performance among existing scheduling algorithms that guarantee packet ordering.
Computational Intelligence in Analog Circuits Design
Authors: Gabriel Oltean, Sorin Hintea, Emilia Sipos
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

This paper presents an optimization algorithm based on computational intelligence techniques, applied to the design of analog circuits. Our approach combines the best qualities of these techniques. Fuzzy sets assure the desired flexibility for the objective functions and a known range of objective function values. High accuracy and low computational complexity are simultaneously present in the neuro-fuzzy models of performances. A powerful global optimization engine is implemented by means of a genetic algorithm. Finally, the proposed algorithm is validated by the design optimization of a CMOS amplifier.
Consumer Phase Shift Simulation Based on Social Psychology and Complex Networks
Authors: Takashi Yoshida, Nobuyuki Tomizawa, Tomohisa Gotoh, Hiroto Iguchi, Kei Sugioka, Ken'ichi Ikeda
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

We have developed the methods for estimating how a new product or a new service will be accepted incontemporary society, considering the effects of word-of-mouth recommendations. These methods are based on a consumer phase shift modeling framework that consists of a consumer agent model and a social network model. Consumer agents, which are classified into four types and six phases, exchange information with each other on a social network. Model parameters were acquired by surveys regarding several new services. These surveys were designed using the snowball sampling technique. We also developed a network generation procedure, applying the idea of complex networks. The multi-agent simulation results proved the feasibility of this framework.
Capture of Lifecycle Information to Support Personal Information Management
Authors: Lasse Lehmann, Christoph Rensing, Ralf Steinmetz
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

Re-use is a key aspect of today's Learning Resource creation. Authors often re-use objects, which they had originally created. Additionally organization of documents has become a complex task and users tend to have more and more problems to manage documents stored on their local computers. With our approach we combine these two aspects by supporting users in their Personal Information Management with information, emerging from re-use processes. We propose a framework capable of capture, management and utilization of this so called lifecycle information and present our implementation for PowerPoint presentations. A first evaluation shows promising results and demonstrates the feasibility and validity of our approach.
E-Business Vocabularies as a Moving Target: Quantifying the Conceptual Dynamics in Domains
Authors: Martin Hepp
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

Most practically relevant domains include some degree of conceptual dynamics, i.e. new conceptual elements arise, and some old ones become irrelevant. This type of change imposes a substantial challenge on building up-to-date domain vocabularies, and models in general. In this paper, we (1) provide a generic simulation model, based on a simple colored Petri-net, for investigating the interplay between conceptual dynamics and model coverage and (2) quantify the dynamics in three selected areas, i.e., for computer components, pharmaceuticals, and for methods, recipes, and procedures in the inorganic chemical technology sector. We can show that all three areas undergo a substantial conceptual dynamics and that this may lead to weak domain coverage in respective vocabularies. Based on these findings, we (3) discuss approaches of how the engineering lag of building domain vocabularies can be reduced.
Building a Fuzzy Ontology of Edutainment Using OWL
Authors: Hua-Mao Gu, Xun Wang, Yun Ling, Jin-Qin Shi
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

OWL Web Ontology Language is a W3C recommended Language for representing machine-readable knowledge with more facilities than other knowledge representation languages. In this paper, we present a Use-Case based Fuzzy Ontology Constructing (UFOC) methodology for the building of edutainment ontology, which is encoded with OWL. Besides, a solution of representing fuzzy relation in OWL is also provided. In the edutainment ontology, two fuzzy relations, DE and AE are discovered, both playing vital roles in property calculation among online computer game.
Combination of N-Grams and Stochastic Context-Free Grammars in an Offline Handwritten Recognition System
Authors: Verónica Romero, Vicente Alabau, Jose Miguel Benedí
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

One area of pattern recognition that is receiving a lot of attention recently is handwritten text recognition. Traditionally, handwritten text recognition systems have been modelled by means of HMM models and n-gram language models. The problem that n-grams present is that they are not able to capture long-term constraints of the sentences. Stochastic context-free grammars (SCFG) can be used to overcome this limitation by rescoring a n-best list generated with the HMM-based recognizer. Howerver, SCFG are known to have problems in the estimation of comlpex real tasks. In this work we propose the use of a combination of n-grams and category-based SCFG together with a word distribution into categories. The category-based approach is thought to simplify the SCFG inference process, while at the same time preserving the description power of the model. The results on the IAM-Database show that this combined scheme outperforms the classical scheme.
Simulating N-Body Systems on the Grid Using Dedicated Hardware
Authors: Derek Groen, Simon Portegies Zwart, Steve Mcmillan, Jun Makino
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

We present performance measurements of direct gravitational N-body simulation on the grid, with and without specialized (GRAPE-6) hardware. Our intercontinental virtual organization consists of three sites, one in Tokyo, one in Philadelphia and one in Amsterdam. We run simulations with up to 196608 particles for a variety of topologies. In many cases, high performance simulations over the entire planet are dominated by network bandwidth rather than latency. Using a global grid of GRAPEs our calculation time remains dominated by communication over the entire range of N, which was limited due to the use of three sites. Increasing the number of particles will result in a more efficient execution and for we expect the computation time to overtake the communication time. We compare our results with a performance model and find that our results are in accordance with the predicted values.
Aestheticization of Flowcharts
Authors: Wioleta Szwoch
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

One of the important issues of diagrams is their aesthetics. In this paper a method of its formalization for freehand drawn flowcharts is proposed. In order to formalize the evaluation of flowcharts' aesthetics a criterion consisting of several measures is proposed. Based on this criterion the algorithms for automatic optimization of flowcharts' appearance are proposed.
Legal Issues for Military Intelligent Decision-Making Technologies
Authors: Anthony Finn
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Intelligent decision-making technologies (IDT) will soon have the capacity to control weapons in a manner that includes decisions regarding target identification and engagement. If permitted, this would provide these systems with the ability to decide which targets to prosecute with lethal force, without any operator intervention. This would mark a sea-change in the role of technology in warfare as the human can be removed from the decision-making loop. There are complex technological and legal issues regarding the development, deployment and exploitation of such systems. This paper outlines our obligations in respect of target discrimination under the Law of Armed Conflict (LOAC) and then uses these principles to discuss the allocation of roles and responsibilities between a human supervisor and the associated IDT. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Summary of the Workshop on Natural Computing and Graph Transformations
Authors: Ion Petre, Grzegorz Rozenberg
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

Natural Computing is a research area concerned with computing taking place in nature and with human-designed computing inspired by nature. It is a fast growing, genuinely interdisciplinary field involving, among others, biology, mathematics and computer science. Graphs and graph transformations are of great interest in this field in several respects. On the one hand, graphs are often used in the modeling of natural processes either as a representation of the hierarchical structures involved in the process or as a way to formalize the features of reality on several levels of abstraction. Several graph related formalisms such as Petri nets, abstract state machines, automata, membrane systems, mobile ambients, etc., are already used as modeling tools for natural processes. On the other hand, in human-designed computing inspired by nature, graph theoretical formulations and problems are often used as benchmarks for the investigation of the potential of the proposed computational paradigms.
MADRE: The Memory-Aware Data Redistribution Engine
Authors: Stephen F. Siegel, Andrew R. Siegel
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

A new class of algorithms is presented for efficiently carrying out many-to-many parallel data redistribution in a memory-limited environment. Key properties of these algorithms are explored, and their performance is compared using idealized benchmark problems. These algorithms form part of a newly developed MPI-based library MADRE (Memory-Aware Data Redistribution Engine), an open source toolkit designed for easy integration with application codes to improve their performance, portability, and scalability.
Expressive Power and Decidability for Memory Logics
Authors: Carlos Areces, Diego Figueira, Santiago Figueira, Sergio Mera
Venue: Proceedings of the 15th international workshop on Logic, Language, Information and Computation (2008)

Taking as inspiration the hybrid logic $\mathcal{HL}({\downarrow})$, we introduce a new family of logics that we call memory logics. In this article we present in detail two interesting members of this family defining their formal syntax and semantics. We then introduce a proper notion of bisimulation and investigate their expressive power (in comparison with modal and hybrid logics). We will prove that in terms of expressive power, the memory logics we discuss in this paper are more expressive than orthodox modal logic, but less expressive than $\mathcal{HL}({\downarrow})$. We also establish the undecidability of their satisfiability problems.
The impact of computer development on the training and utilization of engineers
Authors: Simon Ramo
Venue: Proceedings of the February 4-6, 1953, western computer conference (1953)

Computer development, in the broad sense of automatic intelligence devices for military, business, and industrial applications may some day be the greatest single user of engineers and scientists. Even today, with this field in its infancy, the shortage of properly trained scientists and engineers is the bottleneck. This talk points out the technical difficulty of the new field and the need for training engineers and scientists in new specialties in order to progress rapidly and efficiently in the development. Ultimately, the universities must turn out a new kind of doctor whose studies include the physical sciences, with emphasis on electronics, a study of the human brain, nature's example of a thinking machine, methods and procedures in business and industry, and government and labor rules and regulations. Industry must particularly avoid large programs until and unless capable technical experts can be assigned to the problem. The field is too difficult to be advanced by the average scientist and engineer. The automatic intelligence field properly developed will pay off several times over in the manpower that it uses. For each top technical man assigned for a period of computer development today, the services of scores of people can be spared during an equivalent later period. From the standpoint of the nation's security, as well as to insure the most rapid technical advances, it is justificable to assign a substantial part of the technical effort of this nation's scientific body to computer development. This is a way to increase the nation's brainpower. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
New Chaos Produced from Synchronization of Chaotic Neural Networks
Authors: Zunshui Cheng
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

In this paper, we investigates synchronization dynamics of neural networks. Generalized linear synchronization (GLS) is proposed to acquire a general kind of proportional relationships between two-neuron networks. Under the point of synchronization, we can find that the node has complex dynamics with some interesting characteristics, and some new chaos phenomenons can been found. Numerical simulations show that this method works very well of two-neuron networks with identical Lorenz systems. Also our method can be applied to other systems.
Hybrid Wavelet-RBFNN Model for Monthly Anchovy Catches Forecasting
Authors: Nibaldo Rodriguez, Broderick Crawford, Carlos Castro, Eleuterio Yañez
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

A hybrid method to forecast 1-month ahead monthly anchovy catches in the north area of Chile is proposed in this paper. This method combined two techniques, stationary wavelet transform (SWT) and radial basis function neural network (RBFNN). The observed monthly anchovy catches data is decomposed into two subseries using 1-level SWT and the appropriate subseries are used as inputs to the RBFNN to forecast original anchovy catches time series. The RBFNN architecture is composed of linear and nonlinear weights, which are estimates using the least square method and Levenberg-Marquardt algorithm; respectively. Wavelet-RBFNN based forecasting performance was evaluated by comparing it with classical RBFNN model. The benchmark results shown that a 99% of the explained variance was captured with a reduced parsimony and high speed convergence.
Regional Logic for Local Reasoning about Global Invariants
Authors: Anindya Banerjee, David A. Naumann, Stan Rosenberg
Venue: Proceedings of the 22nd European conference on Object-Oriented Programming (2008)

Shared mutable objects pose grave challenges in reasoning, especially for data abstraction and modularity. This paper presents a novel logic for error-avoiding partial correctness of programs featuring shared mutable objects. Using a first order assertion language, the logic provides heap-local reasoning about mutation and separation, via ghost fields and variables of type `region' (finite sets of object references). A new form of modifies clause specifies write, read, and allocation effects using region expressions; this supports effect masking and a frame rule that allows a command to read state on which the framed predicate depends. Soundness is proved using a standard program semantics. The logic facilitates heap-local reasoning about object invariants: disciplines such as ownership are expressible but not hard-wired in the logic.
CWC: A Clustering-Based Feature Weighting Approach for Text Classification
Authors: Lin Zhu, Jihong Guan, Shuigeng Zhou
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

Most existing text classification methods use the vector space model to represent documents, and the document vectors are evaluated by the TF-IDF method. However, TF-IDF weighting does not take into account the fact that the weight of a feature in a document is related not only to the document, but also to the class that document belongs to. In this paper, we present a Clustering-based feature Weighting approach for text Classification, or CWC for short. CWC takes each class in the training collection as a known cluster, and searches for feature weights iteratively to optimize the clustering objective function, so the best clustering result is achieved, and documents in different classes can be best distinguished by using the resulting feature weights. Performance of CWC is validated by conducting classification over two real text collections, and experimental results show that CWC outperforms the traditional KNN.
XML Schema Representation and Reasoning: A Description Logic Method
Authors: Xiaobing Wu, David Ratcliffe, Mark A. Cameron
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

XML plays a key role in service-oriented computing (SOC). We envisage an environment where knowledge workers are developing semantic correspondences from XML schemas to a target ontology. We would like to use DL reasoning services within this environment to assist the knowledge worker in the following three tasks: establishing the correctness of structural correspondences; the implications of correspondences; and finally, search and selection of schemas with semantic and structural constraints. A knowledge representation method for XML schemas using a description logic language is presented. With this representation method, it is now possible to use the underlying DL reasoning services to achieve our three tasks: correspondence correctness checking through DL model validation; correspondence implication through DL model completion; and finally, semantic and structural search and selection through DL model query.
A CA2 + Dynamics Model of the STDP Symmetry-to-Asymmetry Transition in the CA1 Pyramidal Cell of the Hippocampus
Authors: Vassilis Cutsuridis, Stuart Cobb, Bruce P. Graham
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Recent experimental evidence has reported that the profiles of spike-timing-dependent plasticity (STDP) in the CA1 pyramidal neuron can be classified into two types depending on the location along the stratum radiatum (SR) dendrite: (1) A symmetric STDP profile centered at 0 ms (largest LTP value) with two distinct LTD windows at about ±20ms in the proximal SR dendrite, and (2) an asymmetric one in the distal SR dendrite. Bicuculline application revealed that GABAA is responsible for the symmetry of the STDP curve. We investigate via computer simulations the STDP symmetry-to-asymmetry transition in the proximal SR dendrite. Our findings indicate the transition from symmetry-to-asymmetry is indeed due to decrease of GABAA, but the simulated symmetrical STDP profile is centered at +10ms (and not at 0ms) with two distinct LTD tails at -10ms and +40ms (and not at ±20ms). The simulated LTD tails are strongly dependent on the GABAA conductance.