ppxscal/embedding_network huggingface dataset:
Estimation of radial acoustic wave propagation in relative motion
Authors: Alina Bogoi, Radu D. Rugescu
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

Sound emission and propagation through the moving air in front of aircraft compressors and behind the turbine assemblies is investigated at UPB in a current research program. Results of the sound waves radial propagation in the first stage of the low pressure compressor of the Pratt & Whitney PW-4156A turbofan engine are here presented, analytically investigated in order to offer a better understanding of the efficiency of sound suppression devices. The method of analytical modeling, currently used in inertial reference frames, is extended to non-inertial, fast rotating systems, which better represent the actual situation of the airflow and sound propagation within the jet aircraft engines. A specific Eulerian equations system is proposed and, under certain assumptions, an analytical solution is built, that faces the test of numerical computations and experimental measurements on the aircraft engines noise histograms. A direct application of the study is seen in the appraisal and evaluation of sound suppression equipment developed in joint European aeronautical research projects where Romania is actually involved. The analysis is performed by constantly using the equations of fluid motion in a non-inertial reference system in the desired form for numerical computations. Both the finite difference and characteristic lines methods are considered for evaluation.
A modified T. Chan's preconditioner for Toeplitz systems
Authors: Xiao-Guang Lv, Ting-Zhu Huang, Zhi-Gang Ren
Venue: Computers Mathematics with Applications (2009)

We present a modified T. Chan's preconditioner for solving Toeplitz linear systems by the preconditioned conjugate gradient (PCG) method in this paper. Especially, we give some results when the matrices are Hermitian positive definite Toeplitz matrices. The operation and convergence of the PCG method are discussed. Numerical examples presented illustrate the effectiveness of the preconditioner obtained.
Using R for Computer Simulation and Data Analysis in Biochemistry, Molecular Biology, and Biophysics
Authors: Victor A. Bloomfield
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

Modern biology has become a much more quantitative science, so there is a need to teach a quantitative approach to students. I have developed a course that teaches students some approaches to constructing computational models of biological mechanisms, both deterministic and with some elements of randomness; learning how concepts of probability can help to understand important features of DNA sequences; and applying a useful set of statistical methods to analysis of experimental data. The free, open-source, cross-platform program R serves well as the computer tool for the course, because of its high-level capabilities, excellent graphics, superb statistical capabilities, extensive contributed packages, and active development in bioinformatics. 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
Towards Autonomic Computing: Injecting Self-Organizing and Self-Healing Properties into Java Programs
Authors: M. J. Oudshoorn, M. M. Fuad, D. Deb
Venue: Proceeding of the 2006 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fifth SoMeT_06 (2006)

Autonomic computing is a grand challenge in computing. It aims to produce distributed software that has the properties of self-healing, self-organizing, self-protecting and self-optimizing. This paper focuses on the challenge of injecting only self-healing properties into existing programs that targets the Java Virtual Machine. The byte code is analyzed and additional code is injected to automatically recover from failure such as network or processor failure. A framework to provide autonomic computing support is presented and evaluated to determine its suitability for a fully fledged autonomic computing system.
Punishment Policy Adaptation in a Road Junction Regulation System
Authors: Maite Lopez-Sanchez, Sanja Bauk, Natasa Kovac, Juan A. Rodriguez-Aguilar
Venue: Proceeding of the 2007 conference on Artificial Intelligence Research and Development (2007)

This paper studies the problem of adapting punishment policies in traffic scenarios. It focuses on a two-road junction scenario simulated by means of Simma, a Multi-Agent Based Simulation Tool. Adaptation is based on an adaptive neuro-fuzzy inference system (ANFIS) together with a hybrid learning algorithm (HLA). Basic punishment policy is provided through a knowledge base that specifies the conditions that must hold in order to assign different punishments. The aim of this paper is to show how the ANFIS system can improve this policy unsupervisedly.
To flock or not to flock: the pros and cons of flocking in long-range "migration" of mobile robot swarms
Authors: Fatih Gökçe, Erol Şahin
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

This study investigates the pros and cons of flocking in long-range "migration" of mobile robot swarms under the influence of different factors. We present a flocking behavior consisting of three simple behaviors: heading alignment, proximal control, and alignment to the desired homing direction. The behavior drives a flock of robots from one location to another by sensing the magnetic field of the Earth. We propose that four factors influence the accuracy of reaching a particular location with the proposed behavior; namely, averaging through the heading alignment behavior, the noise in sensing the homing direction, the differences in the characteristics of the individuals, and the disturbances caused by proximal control behavior. In a series of systematic experiments conducted with both physical and simulated robots, we evaluate the effects of these factors in the accuracy of long-range "migrations" of flocks.
A grid data mining architecture for learning classifier systems
Authors: M. F. Santos, W. Mathew, T. Kovacs, H. Santos
Venue: WSEAS Transactions on Computers (2009)

Recently, there is a growing interest among the researchers and software developers in exploring Learning Classifier System (LCS) implemented in parallel and distributed grid structure for data mining, due to its practical applications. The paper highlights the some aspects of the LCS and studying the competitive data mining model with homogeneous data. In order to establish more efficient distributed environment, in the current work, Grid computing architecture is considered a better distributed framework in Supervised Classifier System (UCS). The fundamental structure of this work allows each site of the distributed environment to manage independent UCS and such local sites transmit learning models to the global model for making complete knowledge of the problem. The Boolean 11-multiplexer problems are used for the execution. Hence, the main objective of this work is to keep the average accuracy of distributed mode without loosing accuracy rate compared to models. The experimental results showed that the testing accuracy of distributed mode is higher than other models.
Situational method engineering for governance, risk and compliance information systems
Authors: Anke Gericke, Hans-Georg Fill, Dimitris Karagiannis, Robert Winter
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

Against the background of the current financial crisis and an aftermath of increasing regulation, companies enhance and integrate information systems in the areas of risk management, governance and compliance. Based on experience with isolated and often immature partial solution in these fields, major challenges are the evolution of a suitable risk management solution component as well as the conceptual design of an integrated "Governance, Risk and Compliance" (GRC) approach. Another challenge is the rollout of such an integrated GRC solution. In this paper, we develop and evaluate a situational method that supports the implementation of an integrated GRC solution. The proposed situational method is comprised of 21 method fragments that support conceptual, strategic, organizational, technical, and cultural rollout aspects. Furthermore, method configurations are specified that identify only those method fragments that are relevant for certain roles, e.g. project manager or GRC expert.
Fault diagnosis of power electronic system based on fault gradation and neural network group
Authors: Chengcai Ma, Xiaodong Gu, Yuanyuan Wang
Venue: Neurocomputing (2009)

We propose a new fault diagnosis approach with fault gradation using BP (back-propagation) neural network group consisting of 3 sub BP neural networks. According to the hazard extents and the occurrence frequencies of different faults, the faults are divided into different grades. The higher the fault grade, the larger the number of the used sub neural networks is. Experimental results show that our approach makes the correctness rate of the fault diagnosis rise greatly (from less than 95.0% to 99.5%) and the performance of the whole fault diagnosis system gets much better especially for the on-line complex systems. The approach proposed in this paper also can be extended to other complex fault diagnosis systems, such as mechanical systems.
Primal Discontinuous Galerkin Methods for Time-Dependent Coupled Surface and Subsurface Flow
Authors: Ayçıl Çeşmelioğlu, Béatrice Rivière
Venue: Journal of Scientific Computing (2009)

This paper introduces and analyzes a numerical method based on discontinuous finite element methods for solving the two-dimensional coupled problem of time-dependent incompressible Navier-Stokes equations with the Darcy equations through Beaver-Joseph-Saffman's condition on the interface. The proposed method employs Crank-Nicolson discretization in time (which requires one step of a first order scheme namely backward Euler) and primal DG method in space. With the correct assumption on the first time step optimal error estimates are obtained that are high order in space and second order in time.
Experimental research regarding the dynamic behaviour of the classical guitar
Authors: Ioan Curtu, Mariana D. Stanciu, Raimond Grimberg, Adriana Savin
Venue: Proceedings of the 10th WSEAS international conference on Acoustics & music: theory & applications (2009)

This paper presents the results of some experimental work regarding the dynamic behaviour of the classical guitar manufactured by SC Hora SA Reghin Romania. From the different types of guitars made by the Romanian factory, the guitar with 5 radial braces was the one analyzed. To establish the influence of the neck on the guitar stiffness and its dynamic response, the acoustic box (without the neck and the bridge) and the guitar body (with the neck) were investigated. Chladni figures, frequency responses, power spectrum density and dynamic mass were collected and compared in both cases. This research is useful to improve the acoustic quality of a guitar from the point of view of construction optimization.
Parallelized dynamic service orchestration
Authors: Leo Obrst
Venue:  (2008)

This dissertation describes a technique for parallelizing dynamically formed and semantically-enabled composite web services. Statically linking web services together to form new functionality has been a successful business practice for several years and has produced industry standards including the Business Process Execution Language (BPEL) as well as higher level process flow capabilities such as Business Process Modeling (BPM). The concept of dynamically forming semantically-enabled composite web services is relatively new, but is becoming a popular research area. These research efforts have produced several effective service composition techniques for linking together semantically-enabled web services. However, the performance&mdash;particularly the parallelization&mdash;of these composite services has yet to be addressed. This dissertation describes a novel method for increasing the performance of these dynamically formed composite services with a focus on parallelized execution. The contributions of this dissertation include: (1) A novel method to break apart large, sequential service chains and identify individual sub-chains that can be executed in parallel to improve overall execution performance. This algorithm leverages the graph-oriented relationship capabilities of the Resource Description Framework (RDF) to identify individual, asynchronous service execution chains. (2) An approach to translate a RDF relationship graph to an existing commercial BPM language (jPDL). This helps to close the gap between Semantic Web research and industry. (3) Base line experimental results that gauge the general effectiveness of composite service parallelization. These results are based off of a 12 service sequential composition created by the Xplan service composer and ultimately parsed by the parallelization algorithm. (4) An extension to the jBPM engine that introduces the concepts of "splitter" and "aggregator". These two new introductions assist the parallelization process and offer advantages over the "fork" and "join" node-types that are currently defined in jBPM. (5) Opens the composition process to domains outside of web services. The use of BPM and jPDL allow for the direct execution of Java objects rather than Web Service Description Language (WSDL) described services. This can aid in the development of networked high speed or timing specific environments such as those in scientific workflows.
Introduction to DNA Self-Assembled Computer Design
Authors: Christopher Dwyer, Alvin Lebeck
Venue:  (2007)

Here's a trail-blazing resource that details microchip fabrication using bottom-up DNA self-assembly. This unique book provides a theoretical and practical bridge from today's chip technology to the molecular-scale circuitries that lie ahead. It connects familiar semiconductor concepts to the latest breakthroughs in the use of DNA as construction material, and maps out a detailed method for developing DNA self-assembled computer systems that features case study designs of lightweight self-organizing computer architectures. Probing both the science and the engineering involved, this one-of-a-kind resource reviews current microchip fabrication methods and architectures and discusses fundamentals of nanoscale design and DNA self-assembly. The book addresses self-assembled circuitry and design issues in depth, explaining DNA scaffolding structures and providing techniques for organizing molecular-scale materials, circuits and architectures. This cutting-edge volume explores current technology limitations involving small scale control and large scale randomness, along with architectural challenges to node design, routing, and interfacing to the microscale. You also find case studies of a nanoscale active network architecture and a self-organizing SIMD architecture that give you a clear look at self-assembled system design pointing the way forward. Concluding with a digest of current practices in DNA nanostructure synthesis and insights into the revolutionary design, fabrication, and operational paradigms raised by the concept of "self assembly," this roadmap to DNA microchip synthesis is indispensable for your work in researching and developing nanoscale computer structures, devices, and applications.
Analysis of Muscle and Metabolic Activity during Multiplanar-Cardiofitness Training
Authors: Arrigo Palumbo, Teresa Iona, Vera Gramigna, Antonio Ammendolia, Maurizio Iocco, Gionata Fragomeni
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

Electronic devices have been useful to evaluate muscle fatigue and activation, co-ordination and metabolic consuption among different sports activities. Since these important variables have not been investigated during fitness training, the present study aims to analyze the activity of the major muscles of the lower extremity during training activities on a cardiofitness apparatus (Cardio WaveTM, Technogym® - Gambettole, Italy). This device is able to stimulate the multiplanar movements of lower limbs by combining various types of movement according to the physical principles of human motion. Working simultaneously on three axes by a sliding movement of lower limbs should activate different muscle groups following four positions at different intensity level. Muscles activity and training effectiveness were evaluated by monitoring Electromiography signal, metabolic data, oxygen uptake and heart rate. The goal of this research is to develop a system able to manage different information coming by varius electronic devices.
Tile Reduction: The First Step towards Tile Aware Parallelization in OpenMP
Authors: Ge Gan, Xu Wang, Joseph Manzano, Guang R. Gao
Venue: Proceedings of the 5th International Workshop on OpenMP: Evolving OpenMP in an Age of Extreme Parallelism (2009)

Tiling is widely used by compilers and programmer to optimize scientific and engineering code for better performance. Many parallel programming languages support tile/tiling directly through first-class language constructs or library routines. However, the current OpenMP programming language is tile oblivious, although it is the de facto standard for writing parallel programs on shared memory systems. In this paper, we introduce tile aware parallelization into OpenMP. We propose tile reduction, an OpenMP tile aware parallelization technique that allows reduction to be performed on multi-dimensional arrays. The paper has three contributions: (a) it is the first paper that proposes and discusses tile aware parallelization in OpenMP. We argue that, it is not only necessary but also possible to have tile aware parallelization in OpenMP; (b) the paper introduces the methods used to implement tile reduction, including the required OpenMP API extension and the associated code generation techniques; (c) we have applied tile reduction on a set of benchmarks. The experimental results show that tile reduction can make parallelization more natural and flexible. It not only can expose more parallelism in a program, but also can improve its data locality.
Developing cooperation mechanism for multi-agent systems with Petri nets
Authors: Fu-Shiung Hsieh
Venue: Engineering Applications of Artificial Intelligence (2009)

Although the contract net protocol answers some of the questions in cooperative distributed problem solving (CDPS), it raises many others that CDPS researchers are still trying to answer. In contract net protocol, an agent may play the role of a manager or a bidder. Without a coordination mechanism, a manager may acquire excessive resources from the bidders in forming a collaborative network to execute the assigned task and thus hinder the progress of the tasks assigned to other managers due to resource contention. As a result, application of contract net protocol may not always lead to feasible solutions to accomplish tasks effectively. As a general framework for exchanging messages, the original contract net protocol does not prescribe how agents should cooperate. How to develop a collaborative mechanism to effectively perform the tasks is an important issue. This paper aims to improve the insufficiency of the contract net by developing a mechanism to facilitate cooperation of agents to accomplish their tasks while avoiding undesirable states and enhance the overall system performance in manufacturing systems. To achieve these objectives, detail process models about how agents accomplish their tasks are required. Due to the advantages in modeling concurrent, synchronous and/or asynchronous activities, Petri nets are adopted in this paper. Based on Petri net models, we study the information needed for agents to make cooperative decisions, mechanism to make agents cooperate, and how to enhance the performance in the system level by taking advantage of the agents' cooperation capabilities. To characterize the condition for cooperation, we represent the collaborative networks formed based on the contract net protocol with Petri nets and then find the condition for a collaborative network to be feasible. The feasible condition also serves as a condition for the development of cooperation mechanism for managers. We propose a cooperation mechanism based on the idea of resource donation, including unilateral resource donation and reciprocal resource donation. Implementation architecture has also been proposed to realize our methodology.
MABLE: a framework for learning from natural instruction
Authors: Roger Mailler, Daniel Bryce, Jiaying Shen, Ciaran O'Reilly
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

The Modular Architecture for Bootstrapped Learning Experiments (MABLE) is a system that is being developed to allow humans to teach computers in the most natural manner possible: by using combinations of descriptions, demonstrations, and feedback. MABLE is a highly modular, well-engineered, and extendable system that provides generalized services, such as control, knowledge representation, and execution management. MABLE works by accepting instruction from a teacher and forms concrete learning tasks that are fed to state-of-the-art machine learning algorithms. To make the learning tractable, specialized heuristics, in the form of learning strategies, are used to derive bias from the instruction. The output of the learning is then incorporated into the system's background knowledge to be used in performing tasks or as the basis for simplifying the process of learning difficult concepts. Although still in development, MABLE has already demonstrated the ability to learn four different types of knowledge (definitions, rules, functions, and procedures) from three different modes of student/teacher interaction on two separate, qualitatively different domains. MABLE presents a unique opportunity for machine learning researchers to easily plug in and test algorithms in the context of instructible computing. In the near future, MABLE will be freely available as an open source project.
Top-k queries on uncertain data: on score distribution and typical answers
Authors: Tingjian Ge, Stan Zdonik, Samuel Madden
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Uncertain data arises in a number of domains, including data integration and sensor networks. Top-k queries that rank results according to some user-defined score are an important tool for exploring large uncertain data sets. As several recent papers have observed, the semantics of top-k queries on uncertain data can be ambiguous due to tradeoffs between reporting high-scoring tuples and tuples with a high probability of being in the resulting data set. In this paper, we demonstrate the need to present the score distribution of top-k vectors to allow the user to choose between results along this score-probability dimensions. One option would be to display the complete distribution of all potential top-k tuple vectors, but this set is too large to compute. Instead, we propose to provide a number of typical vectors that effectively sample this distribution. We propose efficient algorithms to compute these vectors. We also extend the semantics and algorithms to the scenario of score ties, which is not dealt with in the previous work in the area. Our work includes a systematic empirical study on both real dataset and synthetic datasets.