ppxscal/embedding_network huggingface dataset:
Making Music with AI: Some examples
Authors: Ramón Lopez de Mantaras
Venue: Proceeding of the 2006 conference on Rob Milne: A Tribute to a Pioneering AI Scientist, Entrepreneur and Mountaineer (2006)

The field of music raises very interesting challenges to computer science and in particular to Artificial Intelligence. Indeed, as we will see, computational models of music need to take into account important elements of advanced human problem solving capabilities such as knowledge representation, reasoning, and learning. In this paper I describe examples of computer programs capable of carrying out musical activities and describe some creative aspects of musical such programs.
Parallelizing Merge Sort onto Distributed Memory Parallel Computers
Authors: Minsoo Jeon, Dongseung Kim
Venue: Proceedings of the 4th International Symposium on High Performance Computing (2009)

Merge sort is useful in sorting a great number of data progressively, especially when they can be partitioned and easily collected to a few processors. Merge sort can be parallelized, however, conventional algorithms using distributed memory computers have poor performance due to the successive reduction of the number of participating processors by a half, up to one in the last merging stage.This paper presents load-balanced parallel merge sort where all processors do the merging throughout the computation. Data are evenly distributed to all processors, and every processor is forced to work in all merging phases. An analysis shows the upper bound of the speedup of the merge time as (P- 1)/log P where P is the number of processors. We have reached a speedup of 8.2 (upper bound is 10.5) on 32-processor Cray T3E in sorting of 4M 32-bit integers.
DataLens: making a good first impression
Authors: Bin Liu, H. V. Jagadish
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

When a database query has a large number of results, the user can only be shown one page of results at a time. One popular approach is to rank results such that the "best" results appear first. This approach is well-suited for information retrieval, and for some database queries, such as similarity queries or under-specified (or keyword) queries with known (or guessable) user preferences. However, standard database query results comprise a set of tuples, with no associated ranking. It is typical to allow users the ability to sort results on selected attributes, but no actual ranking is defined. An alternative approach is not to try to show the estimated best results on the first page, but instead to help users learn what is available in the whole result set and direct them to finding what they need. We present DataLens, a framework that: i) generates the most representative data points to display on the first page without sorting or ranking, ii) allows users to drill-down to more similar items in a hierarchical fashion, and iii) dynamically adjusts the representatives based on the user's new query conditions. To the best of our knowledge, DataLens is the first to allow hierarchical database result browsing and searching at the same time.
A new spice method of modeling of optoelectronic components for optical fiber link transmission
Authors: A. Sonne, A. Ouchar, A. Ghazel
Venue: Proceedings of the 8th WSEAS international conference on Microelectronics, nanoelectronics, optoelectronics (2009)

This paper presents a new method of modeling optoelectronic components such LEDs and laser diode using PSPICE simulator. Often the modeling of these elements utilizes a simple SPICE model of PN junction diode. In this paper we present new method based on the physical parameters of the optoelectronics components. In this work the user introduce directly all the blocks of the optical fiber link in order to simulate the transmission.
On tables of contents and how to recognize them
Authors: Herv&#x00e9; D&#x00e9;jean, Jean-Luc Meunier
Venue: International Journal on Document Analysis and Recognition (2009)

We present a method for structuring a document according to the information present in its different organizational tables: table of contents, tables of figures, etc. This method is based on a two-step approach that leverages functional and formal (layout-based) kinds of knowledge. The functional definition of organizational table, based on five properties, is used to provide a first solution, which is improved in a second step by automatically learning the form of the table of contents. We also report on the robustness and performance of the method and we illustrate its use in a real conversion case.
Architectures for Cooperative Airborne Simultaneous Localisation and Mapping
Authors: Mitch Bryson, Salah Sukkarieh
Venue: Journal of Intelligent and Robotic Systems (2009)

This paper develops active Simultaneous Localisation And Mapping (SLAM) trajectory control strategies for multiple cooperating Unmanned Aerial Vehicles (UAVs) for tasks such as surveillance and picture compilation in Global Positioning System (GPS)-denied environments. Each UAV in the team uses inertial sensor and terrain sensor information to simultaneously localise the UAV while building a point feature map of the surrounding terrain, where map information is shared between vehicles over a data fusion network. Multi-vehicle active SLAM control architectures are proposed that actively plan the trajectories and motions of each of the vehicles in the team based on maximising information in the localisation and mapping estimates. We demonstrate and compare an ideal, centralised architecture, where a central planning node chooses optimal actions for each UAV, and a coordinated, decentralised architecture, where UAVs make their own control decisions based on common shared map information. The different architectures involve varying degrees of complexity and optimality through differing communications and computational requirements. Results are presented using a three-UAV team in a six-degree of freedom multi-UAV simulator.
Computer and Computing Technologies in Agriculture II, Volume 3: The Second IFIP International Conference on Computer and Computing Technologies in Agriculture ... in Information and Communication Technology), 1st edition
Authors: Daoliang Li, Chunjiang Zhao
Venue:  (2009)

This book constitutes the refereed proceedings ofthe 2nd IFIP International Conference on Computer and Computing Technologies in Agricultureheld in Beijing, Chinaon October 18-20, 2008. The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of refereed international conferences in computer science and interdisciplinary fields are featured. These results often precede journal publication and represent the most current research. The principal aim of the IFIP series is to encourage education and the dissemination and exchange of information about all aspects of computing.
A Parallel Implementation of Error Correction SVM with Applications to Face Recognition
Authors: Qingshan Yang, Chengan Guo
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

The Error Correction SVM method is an excellent multiclass classification approach and has been applied to face recognition successfully. Yet, it suffers from the computational complexity. To reduce the computation time of the algorithm, a parallel implementation scheme is presented in the paper in which the training and classification tasks are assigned to multiple processors and run on all the processors simultaneously. The simulation experiments conducted on a local area network using Cambridge ORL face database show that the parallel algorithm given in the paper is effective in speeding up the algorithms of the training and classification while maintaining the recognition accuracy unchanged.
On time-stressed team collaboration
Authors: Xiaocong Fan
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We extend the concept of timed Petri nets to explicitly capture timing constraints and collaboration points along a team process. Several properties of the model are examined. It can be employed as a collaboration mechanism for agents operating in a dynamic, time-stressed environment.
Could the jump diffusion technique enhance the effectiveness of futures hedging models?
Authors: Ming-Yuan Leon Li
Venue: Mathematics and Computers in Simulation (2009)

A multivariate Markov-switching ARCH (MVSWARCH) model in which variance/correlations for futures and spot returns is controlled by a state-varying mechanism is introduced and used to design a state-varying stock index futures hedge ratio. Additionally, a conventional random-variance framework, the MVGARCH (multivariate GARCH) model with a time-varying technique is employed and subjected to a benchmark model. The feasibility of these proposed models is examined using two types of spot positions selected from the U.K. stock markets: (1) the FTSE-100 market index, representing a well-diversified market portfolio, and (2) ten sub-stock indices defined by the Data Stream database, representing the sub-set of the market portfolio. The empirical results are consistent with the following notions. First, when futures and spot returns are simultaneously (individually) based on low or high volatility states, the corresponding correlation measure between futures and spot returns is higher (lower). Second, consistent with prior studies, the in-sample hedging effectiveness tests demonstrated the superior performance of the stat-varying hedge ratio generated by the MVSWARCH model in all cases. However, our empirical results further indicate that the out-of-sample performance of the MVSWARCH-based hedge ratio is statistically marginal when investors hold a well-diversified market portfolio as their spot position and tranquil periods are experienced.
Research concerning the influence of some micro and nano-materials on the wood based product finishing quality in sustainable development conditions
Authors: Loredana Anne-Marie Badescu, Lucia Dumitrescu, Daniela Mihalevschi
Venue: Proceedings of the 1st WSEAS international conference on Nanotechnology (2009)

The authors propose the use of some new hybrid technological materials (organic-inorganic) for finishing of wooden materials, in order to correspond to the concepts of sustainable development, in accordance to European Directives for implementation of Sustainable Development Strategy. Research presents, in a better determinable way, the positive influence of these water based, eco-materials, upon the quality of wood industry finishing products, from technical, aesthetical and environmental protection point of view. In the study are promoted methods and techniques for a high scientific performance investigation, for analyzing and spotting the properties of the new lacquers, based on the proposed micro and nano-materials.
Speckle reduction by adaptive window anisotropic diffusion
Authors: Guojin Liu, Xiaoping Zeng, Fengchun Tian, Zhengzhou Li, Kadri Chaibou
Venue: Signal Processing (2009)

To smooth out speckle noise and preserve edge information in noisy images, a novel algorithm called speckle reduction by adaptive window anisotropic diffusion is proposed. Based on the image's structure, the proposed method can adaptively modulate its window size and orientation. This adaptive window method can calculate the instantaneous coefficient of variation for the edge area with more accuracy than a fixed window method. Furthermore, a novel method for finding the diffusion coefficient is presented. The experimental results show that compared with existing methods, the performance of the proposed method is satisfactory in terms of both speckle suppression and preservation of image details.
Moving Nature-Inspired Algorithms to Parallel, Asynchronous and Decentralised Environments
Authors: Enda Ridge, Daniel Kudenko, Dimitar Kazakov, Edward Curry
Venue: Proceeding of the 2005 conference on Self-Organization and Autonomic Informatics (I) (2005)

This paper motivates research into implementing nature-inspired algorithms in decentralised, asynchronous and parallel environments. These characteristics typify environments such as Peer-To-Peer systems, the Grid and autonomic computing which demand robustness, decentralisation, parallelism, asynchronicity and self-organisation. Nature-inspired systems promise these properties. However, current implementations of nature-inspired systems are only loosely based on their natural counterparts. They are generally implemented as synchronous, sequential, centralised algorithms that loop through passive data structures. For their successes to be relevant to the aforementioned new computing environments, variants of these algorithms must work in truely decentralised, parallel and asynchronous Multi-Agent System (MAS) environments. A general methodology is presented for engineering the transfer of nature-inspired algorithms to such a MAS framework. The concept of pheromone infrastructures is reviewed in light of emerging standards for agent platform architecture and interoperability. These ideas are illustrated using a particularly successful nature-inspired algorithm, Ant Colony System for the Travelling Salesman Problem.
Neural networks for a class of bi-level variational inequalities
Authors: M. H. Xu, M. Li, C. C. Yang
Venue: Journal of Global Optimization (2009)

In this paper, a class of bi-level variational inequalities for describing some practical equilibrium problems, which especially arise from engineering, management and economics, is presented, and a neural network approach for solving the bi-level variational inequalities is proposed. The energy function and neural dynamics of the proposed neural network are defined in this paper, and then the existence of the solution and the asymptotic stability of the neural network are shown. The simulation algorithm is presented and the performance of the proposed neural network approach is demonstrated by some numerical examples.
A combined inductive and deductive sense data extraction and visualisation service
Authors: Mohammad Hammoudeh, Robert Newman, Sarah Mount, Christopher Dennett
Venue: Proceedings of the 2009 international conference on Pervasive services (2009)

Wireless sensor networks (WSNs) have an intimate interaction, via sensors, with the physical environment they operate within. Application domains have a significant effect on applications performance because WSNs are usually deployed to perform application specific tasks. The part of the world with which an application is concerned is defined as that application's domain. The application domain may help scientists to leverage computational power to simulate, visualise, manipulate, predict and gain intuition about monitored phenomenon. In this paper we propose a new visualisation framework, called Multi-Dimensional Application Domain-driven (M-DAD), that elevates the capabilities of the sense data extraction and visualisation mapping service proposed in [1]. M- DAD exploits the application domain to dynamically minimise the mapping service predictive error. It is capable of visualising an arbitrary number of sense modalities. In M-DAD the visualisation performance is improved by utilising the relations between independent sense modalities as well as other parameters of the application domain. M-DAD can meet the goal of reliability and reactivity, and demonstrates satisfactory robustness using the information they collect about the environment they operate within to adapt its behaviour to changes in the environment. Self-adaptation is a fundamental capability of M-DAD which is required to operate in dynamic environments that impose varying functional and performance requirements on WSNs applications. This self-adaptation scheme makes M-DAD more resilient to faults by substituting for faulty nodes, auto-calibrate sensors, and recover form modelling errors. The experimental results demonstrate that M-DAD performs as well or better than mapping services without its extended capabilities.
Comprehensive biomechanical modeling and simulation of the upper body
Authors: Sung-Hee Lee, Eftychios Sifakis, Demetri Terzopoulos
Venue: ACM Transactions on Graphics (TOG) (2009)

We introduce a comprehensive biomechanical model of the human upper body. Our model confronts the combined challenge of modeling and controlling more or less all of the relevant articular bones and muscles, as well as simulating the physics-based deformations of the soft tissues. Its dynamic skeleton comprises 68 bones with 147 jointed degrees of freedom, including those of each vertebra and most of the ribs. To be properly actuated and controlled, the skeletal submodel requires comparable attention to detail with respect to muscle modeling. We incorporate 814 muscles, each of which is modeled as a piecewise uniaxial Hill-type force actuator. To simulate biomechanically-realistic flesh deformations, we also develop a coupled finite element model with the appropriate constitutive behavior, in which are embedded the detailed 3D anatomical geometries of the hard and soft tissues. Finally, we develop an associated physics-based animation controller that computes the muscle activation signals necessary to drive the elaborate musculoskeletal system in accordance with a sequence of target poses specified by an animator.
Bilateral Energy Transfer for high fidelity haptic telemanipulation
Authors: Jordi Artigas, Carsten Preusche, Gerd Hirzinger, Gianni Borghesan, Claudio Melchiorri
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

Among the methods to grant the stability of a telemanipulation system, the bilateral time domain passivity framework has the appealing characteristic to consider both, force and velocity signals exchanged between master and slave systems, and the power introduced or dissipated by the elements that compose the telemanipulation system. In previous works, [2, 3], it has been shown how the bilateral passivity controller (BiPC) can preserve stability when the communication channel that conveys data between master and slave is affected by delay. In this work the authors intend to further explore the possibilities offered by the Bilateral Energy Transfer concept as design guideline, and to refine the control schemes already discussed in [3]. The underlying idea of the Bilateral Energy Transfer is to achieve a transport of energy between the two sides of the real system as faithful to an “ideal” (not delayed) system as allowed by the energy leaks. As energy leak is meant the behavior introduced by the not ideality of some components, such as the communication channel. At the same time, in order to obtain easy-to-use system, the control system must preserve, in some extend, the force, velocity, and position correspondences between master and slave. In order to achieve this goal, a modified version of passivity controller is presented. Its main characteristic is that its correction action aimed at dissipating energy, regarded as generated by energy leaks, is limited and deferred in time. Moreover, a drift compensator is introduced whose role is to solve a drift in position introduced by the operation of the same BiPC; in order to maintain the whole system passive, the action of this controller is bounded to the amount of energy that has been dissipated in excess by the BiPC.
Network Complexity Pyramid with five levels
Authors: Jin-Qing Fang
Venue: International Journal of Systems, Control and Communications (2009)

A network complexity pyramid with five levels is suggest and summarised. From the top level-5 to the bottom level-1 complexity and diversity are increasing but universality and simplicity are decreasing. They can be described in an unification form by four hybrid ratios.
A Bipartite Graph Framework for Summarizing High-Dimensional Binary, Categorical and Numeric Data
Authors: Guanhua Chen, Xiuli Ma, Dongqing Yang, Shiwei Tang, Meng Shuai
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

Data summarization is an important data mining task which aims to find a compact description of a dataset. Emerging applications place special requirements to the data summarization techniques including the ability to find concise and informative summary from high dimensional data, the ability to deal with different types of attributes such as binary, categorical and numeric attributes, end-user comprehensibility of the summary, insensibility to noise and missing values and scalability with the data size and dimensionality. In this work, a general framework that satisfies all of these requirements is proposed to summarize high-dimensional data. We formulate this problem in a bipartite graph scheme, mapping objects (data records) and values of attributes into two disjoint groups of nodes of a graph, in which a set of representative objects is discovered as the summary of the original data. Further, the capability of representativeness is measured using the MDL principle, which helps to yield a highly intuitive summary with the most informative objects of the input data. While the problem of finding the optimal summary with minimal representation cost is computationally infeasible, an approximate optimal summary is achieved by a heuristic algorithm whose computation cost is quadratic to the size of data and linear to the dimensionality of data. In addition, several techniques are developed to improve both quality of the resultant summary and efficiency of the algorithm. A detailed study on both real and synthetic datasets shows the effectiveness and efficiency of our approach in summarizing high-dimensional datasets with binary, categorical and numeric attributes.
Learning from Inconsistencies in an Integrated Cognitive Architecture
Authors: Kai-Uwe Kühnberger, Peter Geibel, Helmar Gust, Ulf Krumnack, Ekaterina Ovchinnikova, Angela Schwering, Tonio Wandmacher
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

Whereas symbol-based systems, like deductive reasoning devices, knowledge bases, planning systems, or tools for solving constraint satisfaction problems, presuppose (more or less) the consistency of data and the consistency of results of internal computations, this is far from being plausible in real-world applications, in particular, if we take natural agents into account. Furthermore in complex cognitive systems, that often contain a large number of different modules, inconsistencies can jeopardize the integrity of the whole system. This paper addresses the problem of resolving inconsistencies in hybrid cognitively inspired systems on both levels, in single processing modules and in the overall system. We propose the hybrid architecture I-Cog as a flexible tool, that is explicitly designed to reorganize knowledge constantly and use occurring inconsistencies as a non-classical learning mechanism.