ppxscal/embedding_network huggingface dataset:
Grid-enabling a vibroacoustic analysis toolkit
Authors: Brian Bentow, Jonathan Dodge, Aaron Homer, Christopher D. Moore, Robert M. Keller, Craig Lee, Mark Thomas, Matthew Presley, Jorge Seidel, Robert Davis, Joseph Betser
Venue: International Journal of High Performance Computing and Networking (2008)

A vibroacoustic analysis toolkit for launch vehicle telemetry was refactored as a service architecture using Globus Toolkit 4.0. We grid-enabled two tools in the analysis flow, managing their remote execution workflow from a desktop client. We examine the performance of the tools and the processing time for the entire tool chain. The results indicate that coordinated communication and execution scheduling as part of workflow management can significantly improve overall efficiency. Our experience also shows that the service-oriented architecture approach, using grid computing tools, can provide a more flexible system design, in addition to improved performance and increased utilisation of resources.
Sircah
Authors: Eoghan D. Harrington, Peer Bork
Venue: Bioinformatics (2008)

Summary: Sircah is a flexible tool for the detection, analysis and visualization of alternative transcripts. It takes as input gene models or spliced alignments and creates a database of alternative transcription events: alternative transcription initiation and polyadenylation, alternative 3′ and 5′ splice-site usage, skipped exons and retained introns. The results can be visualized in a variety of ways, allowing the creation of publication quality images. Availability: The Sircah is available for download under a creative commons license along with additional documentation and a tutorial from http://www.bork.embl.de/Sircah. Contact: bork@embl.de
Soft computing methods applied to the control of a flexible robot manipulator
Authors: B. Subudhi, A. S. Morris
Venue: Applied Soft Computing (2009)

The paper describes use of soft computing methods (fuzzy logic and neural network techniques) in the development of a hybrid fuzzy neural control (HFNC) scheme for a multi-link flexible manipulator. A manipulator with multiple flexible links is a multivariable system of considerable complexity due to the inter-link coupling effects that are present in both rigid and flexible motions. Modelling and controlling the dynamics of such manipulators is therefore difficult. The proposed HFNC scheme generates control actions combining contributions form both a fuzzy controller and a neural controller. The primary loop of the proposed HFNC contains a fuzzy controller and a neural network controller in the secondary loop to compensate for the coupling effects due to the rigid and flexible motion along with the inter-link coupling. It has been ascertained from the present investigation that the proposed soft-computing-based controller works effectively in the tracking control of such a multi-link flexible manipulator. The results are extendable to other multivariable systems of similar complexity.
Instruction Formats and Navigation Aids in Mobile Devices
Authors: Martina Ziefle
Venue: Proceedings of the 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society on HCI and Usability for Education and Work (2008)

Three different instruction formats were examined respecting their usefulness for the navigation through hierarchical menus in mobile phones. 56 middle-aged adults had to solve four mobile phone tasks twice consecutively. Before completing the first trial, they were supported by instruction formats which contained different spatial knowledge types [28]. The first form was a procedural step-by-step instruction delivering landmark and route knowledge. The second instruction consisted of a visualized menu tree, in which the menu path to be taken was marked. By this, mainly survey knowledge but also route information was provided. The third instruction format also used the visualized menu tree. However, in addition to the menu path which had to be taken, also functions' labels were given, conveying landmark, route and survey knowledge. Further, a condition was examined in which no help was given. Dependent variables were navigation effectiveness and efficiency. Overall, the step-by-step condition, the instruction type most often used in technical leaflets, had the smallest effect, especially for users with low spatial visualization abilities. With instruction forms which use diagrammatic visualizations and provide survey knowledge, navigation performance considerably improved.
Improving top-n recommendation techniques using rating variance
Authors: YoungOk Kwon
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

One of the goals in recommender systems is to recommend those items to each user that maximize the user's utility. In this study, we propose new approaches which, in conjunction with any existing recommendation technique, can improve the top-N item selection by taking into account rating variance. We empirically demonstrate how these approaches work with several recommendation techniques, increasing the accuracy of recommendations. We also show how these approaches can generate more personalized recommendations, as measured by the diversity metric. As a result, users can be given a better control to choose whether to receive recommendations with higher accuracy or higher diversity.
Who predicts better?: results from an online study comparing humans and an online recommender system
Authors: Vinod Krishnan, Pradeep Kumar Narayanashetty, Mukesh Nathan, Richard T. Davies, Joseph A. Konstan
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

Algorithmic recommender systems attempt to predict which items a target user will like based on information about the user's prior preferences and the preferences of a larger community. After more than a decade of widespread use, researchers and system users still debate whether such "impersonal" recommender systems actually perform as well as human recommenders. We compare the performance of MovieLens algorithmic predictions with the recommendations made, based on the same user profiles, by active MovieLens users. We found that algorithmic collaborative filtering outperformed humans on average, though some individuals outperformed the system substantially and humans on average outperformed the system on certain prediction tasks.
A hybrid intelligent system for fault detection and sensor fusion
Authors: Mohammad Abdel Kareem Jaradat, Reza Langari
Venue: Applied Soft Computing (2009)

In this paper, an efficient new hybrid approach for multiple sensor fusion and fault detection is proposed, addressing the problem with multiple faults, which is based on conventional fuzzy soft clustering and artificial immune systems. For this new approach, requires no prior knowledge or information about the sensors, or the system behavior, and no learning processes are required. The proposed hybrid approach consists of two main phases. In the first phase a single fuser for the input sensor signals is generated using the fuzzy clustering c-means algorithm. The fused output is based on the cluster centers that contain the maximum number of the input elements. In the second phase a fault detector was generated base on the artificial immune system AIS.
An Analytical Approach to Optimizing the Utility of ESP Games
Authors: Chien-Wei Lin, Kuan-Ta Chen, Ling-Jyh Chen, Irwin King, Jimmy H. M. Lee
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 (2008)

In this paper, we propose an analytical model for computing the utility of ESP games, i.e., the throughput rate of appropriate labels for given puzzles. The model targets generalized games, where the number of players, the consensus threshold, and the stopping condition are variable. Via extensive simulations, we show that our model can accurately predict the stopping condition that will yield the optimal utility of an ESP game under a specific setting. A service provider can therefore utilize the model to ensure that the hosted ESP games produce high-quality labels efficiently, given that the number of players willing to invest time and effort in the game is limited.
A map of the television experience
Authors: Maurice Joseph McGinley
Venue: Proceeding of the 1st international conference on Designing interactive user experiences for TV and video (2008)

This paper presents an analysis of the experience of television based on a definition of experience as 'understanding situated in time'. Citing Heidegger's phenomenological investigations of everyday experiences, as well as tenets from Distributed Cognition, and Activity Theory, the experience of interaction with television is shown to be situated within personal and cultural contexts, which determine the meaning and therefore the quality of the experience. A diagram of television use cases representing television practices is presented, ordered according to proximity to cultural practice. The diagram and method are discussed. The method is recommended as a tool to direct user-interface design and requirements development priorities.
Exponential operator splitting time integration for spectral methods
Authors: Roman Kozlov
Venue: Journal of Computational and Applied Mathematics (2008)

Pseudospectral spatial discretization by orthogonal polynomials and Strang splitting method for time integration are applied to second-order linear evolutionary PDEs. Before such a numerical integration can be used the original PDE is transformed into a suitable form. Trigonometric, Jacobi (and some of their special cases), generalized Laguerre and Hermite polynomials are considered. A double representation of a function (by coefficients of a polynomial expansion and by values at the nodes associated with a suitable quadrature formula) is used for numerical implementation so that it is possible to avoid calculations of matrix exponentials.
Fabrication and characterization of in situ polymerized n-polyaniline films grown on p-Si heterojunctions
Authors: A. Ashery, A. A. M. Farag, M. A. Salem
Venue: Microelectronic Engineering (2008)

This work presents a study on the fabrication and the electrical transport mechanism of the in situ polymerized n-type polyaniline (PANI) grown on p-type Si to form n-polyaniline/p-Si heterojunction devices. The current-voltage-temperature (I-V-T) characteristics of n-PANI/p-Si devices were investigated in the temperature range of 298-373K. These devices showed good rectifying behavior and the temperature dependence of the I-V characteristics were successfully explained by the thermionic mechanism in the narrow potential range, V=
Nonlinear neural network forecasting model for stock index option price: Hybrid GJR-GARCH approach
Authors: Yi-Hsien Wang
Venue: Expert Systems with Applications: An International Journal (2009)

This study integrated new hybrid asymmetric volatility approach into artificial neural networks option-pricing model to improve forecasting ability of derivative securities price. Owing to combines the new hybrid asymmetric volatility method can be reduced the stochastic and nonlinearity of the error term sequence and captured the asymmetric volatility simultaneously. Hence, in the ANNS option-pricing model, the results demonstrate that Grey-GJR-GARCH volatility provides higher predictability than other volatility approaches.
Auditory icons: using sound in computer interfaces
Authors: William W. Gaver
Venue: Human-computer interaction (1986)

There is growing interest in the use of sound to convey information in computer interfaces. The strategies employed thus far have been based on an understanding of sound that leads to either an arbitrary or metaphorical relation between the sounds used and the data to be represented. In this article, an alternative approach to the use of sound in computer interfaces is outlined, one that emphasizes the role of sound in conveying information about the world to the listener. According to this approach, auditory icons, caricatures of naturally occurring sounds, could be used to provide information about sources of data. Auditory icons provide a natural way to represent dimensional data as well as conceptual objects in a computer system. They allow categorization of data into distinct families, using a single sound. Perhaps the most important advantage of this strategy is that it is based on the way people listen to the world in their everyday lives.
Option valuation based on the neural regression model
Authors: Po-Chang Ko
Venue: Expert Systems with Applications: An International Journal (2009)

In this article, a neural regression (NR) model, which produces nonlinear coefficients of multiple regression model based on neural networks, is introduced to capture the option valuation's nonlinear characteristics effectively. The traditional linear regression uses the least-squares estimator to estimate the coefficient of a linear regression and thus may only produce suboptimal solutions. However, Applying neural networks to forecast volatility in option pricing has increased in popularity in recent years since many studies have indicated that the conventional option pricing models are not accurate enough. Our proposed neural regression model devotes to evaluate option values to improve on the tracking error in the measurement of hedging capability. The NR model uses the variables introduced by the Black-Scholes Model and applies the multiple regressions (MR) model to re-price option values. It is worth noting that each corresponding weight coefficient in MR is constructed by a complete neural network rather than by a scalar value. By capturing the nonlinear behaviors of option pricing, our proposed NR model has lower tracking error and better hedging capability than the BS model and other studies.
PhosphoPOINT
Authors: Chia-Ying Yang, Chao-Hui Chang, Ya-Ling Yu, Tsu-Chun Emma Lin, Sheng-An Lee, Chueh-Chuan Yen, Jinn-Moon Yang, Jin-Mei Lai, Yi-Ren Hong, Tzu-Ling Tseng, Kun-Mao Chao, Chi-Ying F. Huang
Venue: Bioinformatics (2008)

Motivation: To fully understand how a protein kinase regulates biological processes, it is imperative to first identify its substrate(s) and interacting protein(s). However, of the 518 known human serine/threonine/tyrosine kinases, 35% of these have known substrates, while 14% of the kinases have identified substrate recognition motifs. In contrast, 85% of the kinases have protein–protein interaction (PPI) datasets, raising the possibility that we might reveal potential kinase–substrate pairs from these PPIs. Results: PhosphoPOINT, a comprehensive human kinase interactome and phospho-protein database, is a collection of 4195 phospho-proteins with a total of 15 738 phosphorylation sites. PhosphoPOINT annotates the interactions among kinases, with their down-stream substrates and with interacting (phospho)-proteins to modulate the kinase–substrate pairs. PhosphoPOINT implements various gene expression profiles and Gene Ontology cellular component information to evaluate each kinase and their interacting (phospho)-proteins/substrates. Integration of cSNPs that cause amino acids change with the proteins with the phosphoprotein dataset reveals that 64 phosphorylation sites result in a disease phenotypes when changed; the linked phenotypes include schizophrenia and hypertension. PhosphoPOINT also provides a search function for all phospho-peptides using about 300 known kinase/phosphatase substrate/binding motifs. Altogether, PhosphoPOINT provides robust annotation for kinases, their downstream substrates and their interaction (phospho)-proteins and this should accelerate the functional characterization of kinomemediated signaling. Availability: PhosphoPOINT can be freely accessed in http://kinase.bioinformatics.tw/ Contact:cyhuang5@ym.edu.tw; kmchao@csie.ntu.edu.tw Supplementary information:Supplementary data are available at Bioinformatics online.
DSM-FI: an efficient algorithm for mining frequent itemsets in data streams
Authors: Hua-Fu Li, Man-Kwan Shan, Suh-Yin Lee
Venue: Knowledge and Information Systems (2008)

Online mining of data streams is an important data mining problem with broad applications. However, it is also a difficult problem since the streaming data possess some inherent characteristics. In this paper, we propose a new single-pass algorithm, called DSM-FI (data stream mining for frequent itemsets), for online incremental mining of frequent itemsets over a continuous stream of online transactions. According to the proposed algorithm, each transaction of the stream is projected into a set of sub-transactions, and these sub-transactions are inserted into a new in-memory summary data structure, called SFI-forest (summary frequent itemset forest) for maintaining the set of all frequent itemsets embedded in the transaction data stream generated so far. Finally, the set of all frequent itemsets is determined from the current SFI-forest. Theoretical analysis and experimental studies show that the proposed DSM-FI algorithm uses stable memory, makes only one pass over an online transactional data stream, and outperforms the existing algorithms of one-pass mining of frequent itemsets.
A class of mean field interaction models for computer and communication systems
Authors: Michel Benaïm, Jean-Yves Le Boudec
Venue: Performance Evaluation (2008)

We consider models of N interacting objects, where the interaction is via a common resource and the distribution of states of all objects. We introduce the key scaling concept of intensity; informally, the expected number of transitions per object per time slot is of the order of the intensity. We consider the case of vanishing intensity, i.e. the expected number of object transitions per time slot is o(N). We show that, under mild assumptions and for large N, the occupancy measure converges, in mean square (and thus in probability) over any finite horizon, to a deterministic dynamical system. The mild assumption is essentially that the coefficient of variation of the number of object transitions per time slot remains bounded with N. No independence assumption is needed anywhere. The convergence results allow us to derive properties valid in the stationary regime. We discuss when one can assure that a stationary point of the ODE is the large N limit of the stationary probability distribution of the state of one object for the system with N objects. We use this to develop a critique of the fixed point method sometimes used in conjunction with the decoupling assumption.
Memory-based neuro-fuzzy system for interpolation of reflection coefficients of printing inks
Authors: Ye. V. Bodyanskiy, N. Ye. Kulishova
Venue: Cybernetics and Systems Analysis (2008)

The problem of interpolation of a two-dimensional function on a nonuniform axial rectangular grid is considered. To solve the problem, a memory-based neuro-fuzzy system is proposed. This system is computationally simple and provides a high-quality interpolation.
Non-stationary power signal processing for pattern recognition using HS-transform
Authors: B. Biswal, P. K. Dash, B. K. Panigrahi
Venue: Applied Soft Computing (2009)

A new approach to time-frequency transform and pattern recognition of non-stationary power signals is presented in this paper. In the proposed work visual localization, detection and classification of non-stationary power signals are achieved using hyperbolic S-transform known as HS-transform and automatic pattern recognition is carried out using GA based Fuzzy C-means algorithm. Time-frequency analysis and feature extraction from the non-stationary power signals are done by HS-transform. Various non-stationary power signal waveforms are processed through HS-transform with hyperbolic window to generate time-frequency contours for extracting relevant features for pattern classification. The extracted features are clustered using Fuzzy C-means algorithm and finally the algorithm is optimized using genetic algorithm to refine the cluster centers. The average classification accuracy of the disturbances is 93.25% and 95.75% using Fuzzy C-means and genetic based Fuzzy C-means algorithm, respectively.
One year of water vapour Raman Lidar measurements at the Andalusian Centre for Environmental Studies (CEAMA)
Authors: J. L. Guerrero-Rascado, B. Ruiz, G. Chourdakis, G. Georgoussis, L. Alados-Arboledas
Venue: International Journal of Remote Sensing (2008)

A Raman Lidar system based on a pulsed Nd: YAG laser has been employed for regular monitoring of the columnar water vapour mixing ratio at the Andalusian Centre for Environmental Studies (CEAMA) (37.16° N, 3.58° W, 680 m a.s.l.), at Granada (southeast of the Iberian Peninsula). This methodology is employed continuously for the first time on the Iberian Peninsula. The Raman Lidar water vapour channel has been calibrated by comparison with simultaneous co-located radio-sounding during a field campaign at El Arenosillo, Huelva, Spain (37.11° N, 6.73° W, 0 m a.s.l.) at the end of June 2006. Since September 2005, systematic water vapour Lidar measurements have been performed. Water vapour Raman Lidar measurements taken at night time over 1 year (from September 2005 to August 2006) have been studied and compared in terms of precipitable water with respect to real radio-sounding data from the two closest radio-sounding stations. In addition, the seasonal variability of the water vapour mixing ratio has been analysed.
The Role of Blackboard-Based Reasoning and Visual Analytics in RESIN's Predictive Analysis
Authors: Dingxiang Liu, Jia Yue, Xiaoyu Wang, Anita Raja, William Ribarsky
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

Knowledge gathering and investigative tasks in open environments can be very complex because the problem-solving context is constantly evolving, and the data may be incomplete, unreliable and/or conflicting. This paper significantly extends our previous work on a mixed-initiative agent by making it capable of assisting humans in foraging task analysis using AI blackboard-based reasoning, visualizations and a mix-initiative user interface. The agent is equipped with the ability to adapt its processing to available resources, deadlines and its current problem-solving context.
An Ontology-Driven Framework for Deploying JADE Agent Systems
Authors: Csongor I. Nyulas, Martin J. O'Connor, Samson W. Tu, David L. Buckeridge, Anna Okhmatovskaia, Mark A. Musen
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

Multi-agent systems have proven to be a powerful technology for building distributed applications. However, the process of designing, configuring and deploying agent-based applications is still primarily a manual one. There is a need for mechanisms and tools to help automate the many development steps required when building these applications. Using the Semantic Web ontology language OWL and the JADE platform we have developed a number of models and software tools that provide an end-to-end solution for designing and deploying agent-based systems. This solution supports the construction of detailed models of agent behavior and the automatic deployment of agents from those models. We illustrate its use in the construction of a multi-agent system that supports the configuration, deployment, and evaluation of analytic methods for detecting disease outbreaks.