ppxscal/embedding_network huggingface dataset:
Using multi-agent platform for pure decentralised business workflows
Authors: Li Guo, Dave Robertson, Yun-Heh Chen-Burger
Venue: Web Intelligence and Agent Systems (2008)

This paper describes the development of a distributed multi-agent workflow enacting mechanism starting from a BPEL4WS specification. Our work demonstrates that a multi-agent interaction protocol (Lightweight Coordination Calculus) can be derived from a BPEL4WS specification to enable pure decentralised business workflows. The key difference between our work and other existing multi-agent based systems is that our approach proposes a pure distributed architecture (no centralised controller/coordinator) for deploying workflow systems in an open environment (internat). Moreover, with our approach, existing workflow developing methodologies and business process models can be adopted in as much as possible for multi-agent system development. Some problems we encountered such as mapping problem between the used business process modelling and multi-agent interaction protocol description languages are addressed.
Optimal vertex ranking of block graphs
Authors: Ruo-Wei Hung
Venue: Information and Computation (2008)

A vertex ranking of an undirected graph G is a labeling of the vertices of G with integers such that every path connecting two vertices with the same label i contains an intermediate vertex with label j>i. A vertex ranking of G is called optimal if it uses the minimum number of distinct labels among all possible vertex rankings. The problem of finding an optimal vertex ranking for general graphs is NP-hard, and NP-hard even for chordal graphs which form a superclass of block graphs. In this paper, we present the first polynomial algorithm which runs in O(n^2log@D) time for finding an optimal vertex ranking of a block graph G, where n and @D denote the number of vertices and the maximum degree of G, respectively.
A new feature selection method for Gaussian mixture clustering
Authors: Hong Zeng, Yiu-Ming Cheung
Venue: Pattern Recognition (2009)

With the wide applications of Gaussian mixture clustering, e.g., in semantic video classification [H. Luo, J. Fan, J. Xiao, X. Zhu, Semantic principal video shot classification via mixture Gaussian, in: Proceedings of the 2003 International Conference on Multimedia and Expo, vol. 2, 2003, pp. 189-192], it is a nontrivial task to select the useful features in Gaussian mixture clustering without class labels. This paper, therefore, proposes a new feature selection method, through which not only the most relevant features are identified, but the redundant features are also eliminated so that the smallest relevant feature subset can be found. We integrate this method with our recently proposed Gaussian mixture clustering approach, namely rival penalized expectation-maximization (RPEM) algorithm [Y.M. Cheung, A rival penalized EM algorithm towards maximizing weighted likelihood for density mixture clustering with automatic model selection, in: Proceedings of the 17th International Conference on Pattern Recognition, 2004, pp. 633-636; Y.M. Cheung, Maximum weighted likelihood via rival penalized EM for density mixture clustering with automatic model selection, IEEE Trans. Knowl. Data Eng. 17(6) (2005) 750-761], which is able to determine the number of components (i.e., the model order selection) in a Gaussian mixture automatically. Subsequently, the data clustering, model selection, and the feature selection are all performed in a single learning process. Experimental results have shown the efficacy of the proposed approach.
A hybrid view of mobility in MANETs: Analytical models and simulation study
Authors: Xianren Wu, Hamid R. Sadjadpour, J. J. Garcia-Luna-Aceves, Hui Xu
Venue: Computer Communications (2008)

We study the effects of node mobility on the wireless links and protocol performance in mobile ad hoc networks (MANETs). First we examine the behavior of links through an analytical framework and develop statistical models to accurately characterize the distribution of lifetime of such wireless links in MANETs. We compute the lifetimes of links through a two-state Markov model, and use these results to model multi-hop paths and topology changes. We show that the analytical solution follows closely the results obtained through discrete-event simulations for two mobility models, namely, random direction and random waypoint mobility models. Finally, we present a comprehensive simulation study that combines the results from the findings in simulations with the analytical results to bring further insight on how different types of mobility translate into protocol performance.
Application of least square method to arbitrary-order problems with separated boundary conditions
Authors: G. B. Loghmani
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper, differential equations of arbitrary order with separated boundary conditions are converted into an optimal control problem. Then a convergent approximate solution is constructed such that the exact boundary conditions are satisfied. In fact it will be shown that for every @e>0, there exists an approximate solution v"@e of B-spline functions such that the corresponding least square error is less than @e>0, and also v"@e satisfies the exact boundary conditions. Some examples are given and the optimal errors are obtained for the sake of comparison.
Knowledge and data flow architecture for reference processing in multimodal dialog systems
Authors: Ali Choumane, Jacques Siroux
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

This paper is concerned with the part of the system dedicated to the processing of the user's designation activities for multimodal search of information. We highlight the necessity of using specific knowledge for multimodal input processing. We propose and describe knowledge modeling as well as the associated processing architecture. Knowledge modeling is concerned with the natural language and the visual context; it is adapted to the kind of application and allows several types of filtering of the inputs. Part of this knowledge is dynamically updated to take into account the interaction history. In the proposed architecture, each input modality is processed first by using the modeled knowledge, producing intermediate structures. Next a fusion of these structures allows the determination of the referent aimed at by using dynamic knowledge. The steps of this last process take into account the possible combinations of modalities as well as the clues carried by each modality (linguistic clues, gesture type). The development of this part of our system is mainly complete and tested.
Perception of low-amplitude haptic stimuli when biking
Authors: Toni Pakkanen, Jani Lylykangas, Jukka Raisamo, Roope Raisamo, Katri Salminen, Jussi Rantala, Veikko Surakka
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

Haptic stimulation in motion has been studied only little earlier. To provide guidance for designing haptic interfaces for mobile use we carried out an initial experiment using C-2 actuators. 16 participants attended in the experiment to find out whether there is a difference in perceiving low-amplitude vibrotactile stimuli when exposed to minimal and moderate physical exertion. A stationary bike was used to control the exertion. Four body locations (wrist, leg, chest and back), two stimulus durations (1000 ms and 2000 ms) and two motion conditions with the stationary bicycle (still and moderate pedaling) were applied. It was found that cycling had significant effect on both the perception accuracy and the reaction times with selected stimuli. Stimulus amplitudes used in this experiment can be used to help haptic design for mobile users.
Exploiting and transferring presentational knowledge assets in R&D organizations
Authors: Sheng-Tun Li, Won-Chen Chang
Venue: Expert Systems with Applications: An International Journal (2009)

Nowadays, how to exploit and transfer the value of knowledge assets effectively has been the primary challenge faced by global R&D organizations. Surprisingly, there seems to be little argument about managing presentational knowledge assets, which are widely used by knowledge workers to present their ideas, proposals, findings and reports. This paper develops the management model and related IT enabling tools that support users to better exploit and transfer presentational knowledge assets. The solution integrates text extractor, slideshow generator, knowledge repository, content-based retrieval and ontology-enabled search engine along with the goal of portraying the search results in a visual navigation form. The performance satisfaction of the proposed system was proved statistically by conducting the user's survey of effectiveness and usability. This solution has demonstrated to be a feasible way for better managing contents, prompting cognitive learning, improving presentation production and presentational knowledge transformation, and consequently facilitates the value leverage of the presentational knowledge assets.
The integrated radiometric correction of optical remote sensing imageries
Authors: S. Kobayashi, K. Sanga-Ngoie
Venue: International Journal of Remote Sensing (2008)

Environmental analysis, management and modelling require detailed and precise land-use/land-cover discrimination as initial conditions of land surface characteristics. With the ultimate goal of accurate land surface classification analysis, we devised a fully image-based and physically based correction method (the Integrated Radiometric Correction (IRC) method) considering both the atmospheric and the topographic effects simultaneously, using the information deduced from the satellite images and 5 m resolution DEM data. The overall process is carried out in four steps: (i) calculation of the radiance/irradiance relational expression for horizontal surfaces, (ii) devising the radiance/irradiance relational expression for inclined surfaces, (iii) derivation of solar and land geometric parameters from DEM data, as well as the calculation of the topographic correction factor (A-factor) and the atmospheric transmittance functions, and (iv) retrieval of the corrected surface reflectance and radiance. Using Landsat/ETM+ satellite data, the performance of the formulated IRC method is evaluated visually and statistically. Visual evaluation of radiometrically corrected images shows significant improvements for each band as well as for various bands composites, while the independence between the corrected surface reflectance and radiance, and the topography (incidence angle (i) or solar illumination (cos i)) is shown by very weak correlation coefficients as compared with non-corrected data.
On generating near-optimal tableaux for conditional functional dependencies
Authors: Lukasz Golab, Howard Karloff, Flip Korn, Divesh Srivastava, Bei Yu
Venue: Proceedings of the VLDB Endowment (2008)

Conditional functional dependencies (CFDs) have recently been proposed as a useful integrity constraint to summarize data semantics and identify data inconsistencies. A CFD augments a functional dependency (FD) with a pattern tableau that defines the context (i.e., the subset of tuples) in which the underlying FD holds. While many aspects of CFDs have been studied, including static analysis and detecting and repairing violations, there has not been prior work on generating pattern tableaux, which is critical to realize the full potential of CFDs. This paper is the first to formally characterize a "good" pattern tableau, based on naturally desirable properties of support, confidence and parsimony. We show that the problem of generating an optimal tableau for a given FD is NP-complete but can be approximated in polynomial time via a greedy algorithm. For large data sets, we propose an "on-demand" algorithm providing the same approximation bound, that outperforms the basic greedy algorithm in running time by an order of magnitude. For ordered attributes, we propose the range tableau as a generalization of a pattern tableau, which can achieve even more parsimony. The effectiveness and efficiency of our techniques are experimentally demonstrated on real data.
Adaptive learning of dynamic Bayesian networks with changing structures by detecting geometric structures of time series
Authors: Kaijun Wang, Junying Zhang, Fengshan Shen, Lingfeng Shi
Venue: Knowledge and Information Systems (2008)

A dynamic Bayesian network (DBN) is one of popular approaches for relational knowledge discovery such as modeling relations or dependencies, which change over time, between variables of a dynamic system. In this paper, we propose an adaptive learning method (autoDBN) to learn DBNs with changing structures from multivariate time series. In autoDBN, segmentation of time series is achieved first through detecting geometric structures transformed from time series, and then model regions are found from the segmentation by designed finding strategies; in each found model region, a DBN model is established by existing structure learning methods; finally, model revisiting is developed to refine model regions and improve DBN models. These techniques provide a special mechanism to find accurate model regions and discover a sequence of DBNs with changing structures, which are adaptive to changing relations between multivariate time series. Experimental results on simulated and real time series show that autoDBN is very effective in finding accurate/reasonable model regions and gives lower error rates, outperforming the switching linear dynamic system method and moving window method.
Some higher-order modifications of Newton's method for solving nonlinear equations
Authors: YoonMee Ham, Changbum Chun, Sang-Gu Lee
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper we consider constructing some higher-order modifications of Newton's method for solving nonlinear equations which increase the order of convergence of existing iterative methods by one or two or three units. This construction can be applied to any iteration formula, and per iteration the resulting methods add only one additional function evaluation to increase the order. Some illustrative examples are provided and several numerical results are given to show the performance of the presented methods.
A comparison of multi-agents competing for trading agents competition
Authors: Dan Mancas, Stefan Udristoiu, Ecaterina-Irina Manole, Bogdan Lapadat
Venue: WSEAS Transactions on Computers (2008)

We present a comparative analysis for several multi-agents participating in Trading Agents Competition, Classic. The game is first partitioned into separate modules, for which distinct strategies may be developed. The strategies used are taken into consideration both individually and in relation with other agents, but also the game medium. Conclusions regarding possible improvements, better strategies and potential weaknesses are driven from each agent analysis. Alternatives like static market algorithms vs. dynamic market algorithms are considered in detail and advantages and disadvantages are discussed. Also a discussion of TAC market and possibilities for the stochastic system approximation with a deterministic one is realized.
EDZL scheduling analysis
Authors: Theodore P. Baker, Michele Cirinei, Marko Bertogna
Venue: Real-Time Systems (2008)

A schedulability test is derived for the global Earliest Deadline Zero Laxity (EDZL) scheduling algorithm on a platform with multiple identical processors. The test is sufficient, but not necessary, to guarantee that a system of independent sporadic tasks with arbitrary deadlines will be successfully scheduled, with no missed deadlines, by the multiprocessor EDZL algorithm. Global EDZL is known to be at least as effective as global Earliest-Deadline-First (EDF) in scheduling task sets to meet deadlines. It is shown, by testing on large numbers of pseudo-randomly generated task sets, that the combination of EDZL and the new schedulability test is able to guarantee that far more task sets meet deadlines than the combination of EDF and known EDF schedulability tests.In the second part of the paper, an improved version of the EDZL-schedulability test is presented. This new algorithm is able to efficiently exploit information on the slack values of interfering tasks, to iteratively refine the estimation of the interference a task can be subjected to. This iterative algorithm is shown to have better performance than the initial test, in terms of schedulable task sets detected.
Storage Estimation and Design Space Exploration Methodologies for the Memory Management of Signal Processing Applications
Authors: F. Balasa, P. G. Kjeldsberg, A. Vandecappelle, M. Palkovic, Q. Hu, H. Zhu, F. Catthoor
Venue: Journal of Signal Processing Systems (2008)

The storage requirements in data-dominated signal processing systems, whose behavior is described by array-based, loop-organized algorithmic specifications, have an important impact on the overall energy consumption, data access latency, and chip area. This paper gives a tutorial overview on the existing techniques for the evaluation of the data memory size, which is an important step during the early stage of system-level exploration. The paper focuses on the most advanced developments in the field, presenting in more detail (1) an estimation approach for non-procedural specifications, where the reordering of the loop execution within loop nests can yield significant memory savings, and (2) an exact computation approach for procedural specifications, with relevant memory management applications --- like, measuring the impact of loop transformations on the data storage, or analyzing the performance of different signal-to-memory mapping models. Moreover, the paper discusses typical memory management trade-offs --- like, for instance, between storage requirement and number of memory accesses --- taken into account during the exploration of the design space by loop transformations in the system specification.
PRIMEGENS-v2
Authors: Gyan P. Srivastava, Juyuan Guo, Huidong Shi, Dong Xu
Venue: Bioinformatics (2008)

Motivation: DNA methylation plays important roles in biological processes and human diseases, especially cancers. High-throughput bisulfite genomic sequencing based on new generation of sequencers, such as the 454-sequencing system provides an efficient method for analyzing DNA methylation patterns. The successful implementation of this approach depends on the use of primer design software capable of performing genome-wide scan for optimal primers from in silico bisulfite-treated genome sequences. We have developed a method, which fulfills this requirement and conduct primer design for sequences including regions of given promoter CpG islands. Results: The developed method has been implemented using the C and JAVA programming languages. The primer design results were tested in the PCR experiments of 96 selected human DNA sequences containing CpG islands in the promoter regions. The results indicate that this method is efficient and reliable for designing sequence-specific primers. Availability: The sequence-specific primer design for DNA meth-ylated sequences including CpG islands has been integrated into the second version of PRIMEGENS as one of the primer design features. The software is freely available for academic use at http://digbio.missouri.edu/primegens/. Contact: xudong@missouri.edu
kNN CF: a temporal social network
Authors: Neal Lathia, Stephen Hailes, Licia Capra
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

Recommender systems, based on collaborative filtering, draw their strength from techniques that manipulate a set of user-rating profiles in order to compute predicted ratings of unrated items. There are a wide range of techniques that can be applied to this problem; however, the k-nearest neighbour (kNN) algorithm has become the dominant method used in this context. Much research to date has focused on improving the performance of this algorithm, without considering the properties that emerge from manipulating the user data in this way. In order to understand the effect of kNN on a user-rating dataset, the algorithm can be viewed as a process that generates a graph, where nodes are users and edges connect similar users: the algorithm generates an implicit social network amongst the system subscribers. Temporal updates of the recommender system will impose changes on the graph. In this work we analyse user-user kNN graphs from a temporal perspective, retrieving characteristics such as dataset growth, the evolution of similarity between pairs of users, the volatility of user neighbourhoods over time, and emergent properties of the entire graph as the algorithm parameters change. These insights explain why certain kNN parameters and similarity measures outperform others, and show that there is a surprising degree of structural similarity between these graphs and explicit user social networks.
A Fitts Law comparison of eye tracking and manual input in the selection of visual targets
Authors: Roel Vertegaal
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

We present a Fitts' Law evaluation of a number of eye tracking and manual input devices in the selection of large visual targets. We compared performance of two eye tracking techniques, manual click and dwell time click, with that of mouse and stylus. Results show eye tracking with manual click outperformed the mouse by 16%, with dwell time click 46% faster. However, eye tracking conditions suffered a high error rate of 11.7% for manual click and 43% for dwell time click conditions. After Welford correction eye tracking still appears to outperform manual input, with IPs of 13.8 bits/s for dwell time click, and 10.9 bits/s for manual click. Eye tracking with manual click provides the best tradeoff between speed and accuracy, and was preferred by 50% of participants. Mouse and stylus had IPs of 4.7 and 4.2 respectively. However, their low error rate of 5% makes these techniques more suitable for refined target selection.
The implications of method placement on API learnability
Authors: Jeffrey Stylos, Brad A. Myers
Venue: Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering (2008)

To better understand what makes Application Programming Interfaces (APIs) hard to use and how to improve them, recent research has begun studying programmers' strategies and use of APIs. It was found that method placement --- on which class or classes a method is placed --- can have large usability impact in object-oriented APIs. This was because programmers often start their exploration of an API from one "main" object, and were slower finding other objects that were not referenced in the methods of the main object. For example, while mailServer.send(mailMessage) might make sense, if programmers often begin their API explorations from the MailMessage class, then this makes it harder to find the MailServer class than the alternative mailMessage.send(mailServer). This is interesting because many real APIs place methods essential to common objects on other, helper objects. Alternate versions of three different APIs were compared, and it was found that programmers gravitated toward the same starting classes and were dramatically faster --- between 2 to 11 times --- combining multiple objects when a method on the starting class referred to the other class.