ppxscal/embedding_network huggingface dataset:
A quick MST-based algorithm to obtain Pathfinder networks (&infin;, n - 1)
Authors: Arnaud Quirin, Oscar Cordón, Vicente P. Guerrero-Bote, Benjamín Vargas-Quesada, Felix Moya-Anegón
Venue: Journal of the American Society for Information Science and Technology (2008)

Network scaling algorithms such as the Pathfinder algorithm are used to prune many different kinds of networks, including citation networks, random networks, and social networks. However, this algorithm suffers from run time problems for large networks and online processing due to its O(n4) time complexity. In this article, we introduce a new alternative, the MST-Pathfinder algorithm, which will allow us to prune the original network to get its PFNET(&infin;, n - 1) in just O(n2 &middot; log n) time. The underlying idea comes from the fact that the union (superposition) of all the Minimum Spanning Trees extracted from a given network is equivalent to the PFNET resulting from the Pathfinder algorithm parameterized by a specific set of values (r = &infin; and q = n - 1), those usually considered in many different applications. Although this property is well-known in the literature, it seems that no algorithm based on it has been proposed, up to now, to decrease the high computational cost of the original Pathfinder algorithm. We also present a mathematical proof of the correctness of this new alternative and test its good efficiency in two different case studies: one dedicated to the post-processing of large random graphs, and the other one to a real world case in which medium networks obtained by a cocitation analysis of the scientific domains in different countries are pruned. &copy; 2008 Wiley Periodicals, Inc.
Improvement of Jarvis-Patrick Clustering Based on Fuzzy Similarity
Authors: Agnes Vathy-Fogarassy, Attila Kiss, Janos Abonyi
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

Different clustering algorithms are based on different similarity or distance measures (e.g. Euclidian distance, Minkowsky distance, Jackard coefficient, etc.). Jarvis-Patrick clustering method utilizes the number of the common neighbors of the k-nearest neighbors of objects to disclose the clusters. The main drawback of this algorithm is that its parameters determine a too crisp cutting criterion, hence it is difficult to determine a good parameter set. In this paper we give an extension of the similarity measure of the Jarvis-Patrick algorithm. This extension is carried out in the following two ways: (i) fuzzyfication of one of the parameters, and (ii) spreading of the scope of the other parameter. The suggested fuzzy similarity measure can be applied in various forms, in different clustering and visualization techniques (e.g. hierarchical clustering, MDS, VAT). In this paper we give some application examples to illustrate the efficiency of the use of the proposed fuzzy similarity measure in clustering. These examples show that the proposed fuzzy similarity measure based clustering techniques are able to detect clusters with different sizes, shapes and densities. It is also shown that the outliers are also detectable by the proposed measure.
Partial derivative evaluating formulae from a data given on the nodes of a regular planar grid
Authors: Aysegül Kurşunlu, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

This study focuses on the evaluation of partial derivatives of a bivariate function with respect to its arguments from the function's known values at the nodes of a rectangular grid. Although evaluation is based on the truncated Taylor series expansion of the function at a midpoint in its analyticity domain, it can also be related to Lagrange polynomials despite we do not focus on this direction here. We use direct products of the vectors (and matrices). This is due to cartesian product nature of the data domain. Direct product utilization reduces computational complexity since it somehow enables us to deal with each dimension independently. What we have developed and revealed here can be applied to the multivariances beyond the bivariate case without any remarkable difficulty.
Improved pairwise alignment of genomic dna
Authors: Robert S. Harris
Venue:  (2007)

Advances in DNA sequencing technology have fueled a rapid increase in the number of sequenced vertebrate genomes, and we anticipate an explosion in the number of genomes sequenced in the near future. Detecting similarities between genomes is a valuable technique in discovering functional elements, and sequence alignment is the primary tool for discovering similarities. The quality of alignments is affected by several user-specified control parameters. The parameters are so little understood that most users simply use default settings. We seek to change that, to have the program automatically infer appropriate parameter choices from statistics derived automatically from the sequences. We introduce a program, INFERZ, which addresses part of the inference problem, inferring substitution and gap scores according to a mathematically sound model. Further, we explore the usefulness of iterating inferred scores to convergence. We test this process on both simulated and actual genomic data, and show that iteration will converge in general, but found that converged scores were not a consistent improvement. INFERZ has a synergistic relationship with LASTZ, our improved drop-in replacement for the widely used alignment program BLASTZ. INFERZ makes repeated calls to LASTZ to test score sets, and LASTZ provides the user an option to have INFERZ decide what scoring parameters to use. Compared to BLASTZ, LASTZ adds a richer set of seeding strategy choices, supports alignment to probabilistic sequences and reduces memory requirements. Additionally, disciplined software techniques make it a better platform for continued experimentation.
Selective Attention Model of Moving Objects
Authors: Roman Borisyuk, David Chik, Yakov Kazanovich
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Tracking moving objects is a vital visual task for the survival of an animal. We describe oscillatory neural network models of visual attention with a central element that can track a moving target among a set of distracters on the screen. At the initial stage, the model forms focus of attention on an arbitrary object that is considered as a target. Other objects are treated as distracters. We present here two models: 1) synchronisation based AMCO model of phase oscillators and 2) spiking neural model which is based on the idea of resource-limited parallel visual pointers. Selective attention and the tracking process are represented by partial synchronization between the central unit and subgroup of peripheral elements. The simulation results are in overall agreement with the findings from psychological experiments: overlapping between target and distractor is the main source of error. Future investigations include the dependence between tracking performance and neuron frequency.
A Practical Clustering Algorithm
Authors: Wei Li, Haohao Li, Jianye Chen
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

We present a novel clustering algorithm (SDSA algorithm) based on the concept of the short distance of the consecutive points and the small angle between the consecutive vectors formed by three adjacent points. Not only the proposed SDSA algorithm is suitable for almost all test data sets used by Chung and Liu for point symmetry-based K-means algorithm (PSK algorihtm) and their newly proposed modified point symmetry-based K-means algorithm (MPSK algorithm ), the proposed SDSA algorithm is also suitable for many other cases where the PSK algorihtm and MPSK algorithm can not be well performed. Based on some test data sets, experimental results demonstrate that our proposed SDSA algorithm is rather encouraging when compared to the previous PSK algorithm and MPSK algorithm.
Using temporal correlation for fault localization in dynamically changing networks
Authors: Maitreya Natu, Adarshpal S. Sethi
Venue: International Journal of Network Management (2008)

A mobile ad hoc network creates a dynamic environment where node mobility can cause periodic changes in routes. Most existing fault localization algorithms assume availability of a complete and/or deterministic dependency model. Such assumptions cannot be made in the dynamically changing networks. This paper is aimed at developing a fault diagnosis architecture and algorithm to address the issue of dynamically changing dependencies in networks. We propose an architecture to capture the changes in dependencies and introduce a temporal correlation algorithm to perform fault diagnosis with the dynamically changing dependency information. We present an experimental evaluation of our work through simulation results using Qualnet.
Dynamic Polymorphic Agents Scheduling and Execution Using Artificial Immune Systems
Authors: Leonardo M. Honório, Michael Vidigal, Luiz E. Souza
Venue: Proceedings of the 7th international conference on Artificial Immune Systems (2008)

When a set of heterogeneous agents is considered to solve different kinds of problems, it is very challenging to specify the necessary number of elements, which functionally of each one will be used and the schedule of these actions in order to solve these problems. To deal with scenarios like this, the present article suggests an innovation at the Intelligent Agent Theory, a new concept called Dynamic Polymorphic Agent (DPA). This approach implies on the dynamic generation of one agent, built from the cooperation of existing agents and specific to fulfill the demanding task. To create this new entity, a monitor identifies and reads information regarding the functionalities of available agents present in the scene and, when a new problem is presented, it generates a task list to solve it. This list and the agents whose functionalities are necessary to solve the problem generate the new polymorphic agent. To fulfill this approach, two major paradigms are used: Aspect-Oriented Program (AOP) and Artificial Immune System (AIS).
FAST: acceleration from theory to practice
Authors: S&#x00e9;bastien Bardin, Alain Finkel, J&#x00e9;r&#x00f4;me Leroux, Laure Petrucci
Venue: International Journal on Software Tools for Technology Transfer (STTT) (2008)

Fast acceleration of symbolic transition systems (Fast) is a tool for the analysis of systems manipulating unbounded integer variables. We check safety properties by computing the reachability set of the system under study. Even if this reachability set is not necessarily recursive, we use innovative techniques, namely symbolic representation, acceleration and circuit selection, to increase convergence. Fast has proved to perform very well on case studies. This paper describes the tool, from the underlying theory to the architecture choices. Finally, Fast capabilities are compared with those of other tools. A range of case studies from the literature is investigated.
A Methodology for Exploring Association Models
Authors: Alipio Jorge, João Poças, Paulo J. Azevedo
Venue: Visual Data Mining: Theory, Techniques and Tools for Visual Analytics (2008)

Visualization in data mining is typically related to data exploration. In this chapter we present a methodology for the post processing and visualization of association rule models. One aim is to provide the user with a tool that enables the exploration of a large set of association rules. The method is inspired by the hypertext metaphor. The initial set of rules is dynamically divided into small comprehensible sets or pages, according to the interest of the user. From each set, the user can move to other sets by choosing one appropriate operator. The set of available operators transform sets of rules into sets of rules, allowing focusing on interesting regions of the rule space. Each set of rules can also be then seen with different graphical representations. The tool is web-based and dynamically generates SVG pages to represent graphics. Association rules are given in PMML format.
Correlated Query Process and P2P Execution
Authors: Qiming Chen, Meichun Hsu
Venue: Proceedings of the 1st international conference on Data Management in Grid and Peer-to-Peer Systems (2008)

A technical trend in supporting data intensive applications is to push-down them to database engines by wrapping computations with User Defined Functions (UDFs) callable from the SQL interface. For seamlessly integrating applications into SQL queries, we introduce a special kind of UDFs with both input and output as relations, or row sets, called Relation Valued Functions (RVFs). As a single SQL statement has limited expressive power on complex data flows and control flows, we propose the notion of Correlated Query Process (CQP), for specifying an application at the process level, by several queries and RVFs with interleaved steps.We further extend this notion to Collaborative CQP with multiple participating parties which have correlated but separate goals. A truly P2P execution model is proposed, under which the logical execution of a collaborative CQP consists of a set of individual peer CQP executions run by the participating parties. These peer executions are based on the same CQP template; but each peer represents a designated role, it actively processes the steps belong to that role, and skip the steps not belonging to that role. They synchronize peer CQP executions by passing the query return messages. This collaborative process execution model represents a shift from coordinator based distributed query processing to truly P2P collaboration.This work represents an initial step to the synthesis of relational operation, UDF and business process. We further envisage that the proposed P2P CQP execution model will have impact not only on inter-enterprise collaboration but also on the cooperation of multiple share-nothing data servers.
Change Detection of Remote Sensing Images with Semi-supervised Multilayer Perceptron
Authors: Swarnajyoti Patra, Susmita Ghosh, Ashish Ghosh
Venue: Fundamenta Informaticae (2008)

A context-sensitive change-detection technique based on semi-supervised learning with multilayer perceptron is proposed here. In order to take contextual information into account, input patterns are generated considering each pixel of the difference image along with its neighboring pixels. A heuristic technique is suggested to identify a few initial labeled patterns without using ground truth information. The network is initially trained using these labeled data. The unlabeled patterns are iteratively processed by the already trained perceptron to obtain a soft class label. Experimental results, carried out on two multispectral and multitemporal remote sensing images, confirm the effectiveness of the proposed approach.
Exponential family predictive representations of state
Authors: Satinder Singh Baveja
Venue:  (2008)

Many agent-environment interactions can be framed as dynamical systems in which agents take actions and receive observations. These dynamical systems are diverse, representing such things as a biped walking, a stock price changing over time, the trajectory of a missile, or the shifting fish population in a lake. Often, interacting successfully with the environment requires the use of a model, which allows the agent to predict something about the future by summarizing the past. Two of the basic problems in modeling partially observable dynamical systems are selecting a representation of state and selecting a mechanism for maintaining that state. This thesis explores both problems from a learning perspective: we are interested in learning a predictive model directly from the data that arises as an agent interacts with its environment. This thesis develops models for dynamical systems which represent state as a set of statistics about the short-term future, as opposed to treating state as a latent, unobservable quantity. In other words, the agent summarizes the past into predictions about the short-term future, which allow the agent to make further predictions about the infinite future. Because all parameters in the model are defined using only observable quantities, the learning algorithms for such models are often straightforward and have attractive theoretical properties. We examine in depth the case where state is represented as the parameters of an exponential family distribution over a short-term window of future observations. We unify a number of different existing models under this umbrella, and predict and analyze new models derived from the generalization. One goal of this research is to push models with predictively defined state towards real-world applications. We contribute models and companion learning algorithms for domains with partial observability, continuous observations, structured observations, high-dimensional observations, and/or continuous actions. Our models successfully capture standard POMDPs and benchmark nonlinear timeseries problems with performance comparable to state-of-the-art models. They also allow us to perform well on novel domains which are larger than those captured by other models with predictively defined state, including traffic prediction problems and domains analogous to autonomous mobile robots with camera sensors.
M-learning and knowledge management in the Grade 1-9 curriculum
Authors: Wen-Jiuh Chiang, Rong-Jyue Fang, Zhen-Gang Chen, Hua-Lin Tsai, Chiao-Pin Lin, Chien-Chine Chien-Chine
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

The Study of this research is to realize the the study of applying m-learning and knowledge management in the Grade 1-9 curriculum, and viewpoints of the related questions of the Grade 1-9 curriculum, and to offer the practical suggestions. There are "questionnaire" and "interview" involved in this study. The public elementary school teachers in Kaohsiung city are the main objects in this research. After arranging these data, we obtain some suggestions from the findings of this study. Actually, the main conclusions of the study are as follows: 1. Most of the elementary school teachers tend to stand for the state enforcement of the Grade1-9 curriculum. 2. There is a significantly different level among these items (sexuality, age and position in school) in the understanding of the theory of the Grade1-9 curriculum of the elementary school teachers. 3. There is a significantly different level at the item (total classes in school) in the understanding of the concept of the Grade1-9 curriculum of the elementary school teachers. 4. There is a significantly different level among these items (sexuality, highest diploma and total classes in school) in the understanding of the curriculum innovation of the Grade1-9 curriculum of the elementary school teachers. 5. There is a significantly different level at the item (different background) in the thoughts of the elementary school teachers on forming a complete set and the attitude towards reform. 6. There is a different level at the item (different background) in the current executive situation of the Grade1-9 curriculum of the elementary school teachers. Finally, according to the conclusions of the study, we hope to offer some suggestions for teacher-training institutions, educational authority, and administrators of elementary school, elementary school teachers and the future research.
Leveraging the Social Semantic Web in Intelligent Tutoring Systems
Authors: Jelena Jovanović, Carlo Torniai, Dragan Gašević, Scott Bateman, Marek Hatala
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Today's technology enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially-oriented services. In this context, a crucial issue for education systems in general, and for ITSs in particular, is related to the ability of leveraging these new paradigms for creating, maintaining and sharing the knowledge that these systems embed. This will enable learning environments to benefit from shared information from disparate systems, which is related to learning content and student activities, so that the overall complexity of system development and maintenance would be reduced while at the same time improving the capability of personalization, context-awareness, collaboration, and feedback provisioning. In this paper, we investigate how the Social Semantic Web can be leveraged for enabling and easing this process. This paper analyzes each ITS module, showing how it can benefit from the Social Semantic Web paradigm.
Auditory distance perception in an acoustic pipe
Authors: Federico Fontana, Davide Rocchesso
Venue: ACM Transactions on Applied Perception (TAP) (2008)

In a study of auditory distance perception, we investigated the effects of exaggeration the acoustic cue of reverberation where the intensity of sound did not vary noticeably. The set of stimuli was obtained by moving a sound source inside a 10.2-m long pipe having a 0.3-m diameter. Twelve subjects were asked to listen to a speech sound while keeping their head inside the pipe and then to estimate the egocentric distance from the sound source using a magnitude production procedure. The procedure was repeated eighteen times using six different positions of the sound source. Results show that the point at which perceived distance equals physical distance is located approximately 3.5 m away from the listening point, with an average range of distance estimates of approximately 3.3 m, i.e., 1.65 to 4.9 m. The absence of intensity cues makes the acoustic pipe a potentially interesting modeling paradigm for the design of auditory interfaces in which distance is rendered independently of loudness. The proposed acoustic environment also confirms the known unreliability of certain distance cues.
Assisting Tourists on the Move- An Evaluation of Mobile Tourist Guides
Authors: Christoph Grün, Hannes Werthner, Birgit Pröll, Werner Retschitzegger, Wieland Schwinger
Venue: Proceedings of the 2008 7th International Conference on Mobile Business (2008)

The penetration of high-end mobile devices equipped with GPS and enhanced with multimedia features together with decreasing mobile data prices have resulted in larger usage of mobile services. One of the application domains particularly well-suited for mobile services is tourism, not least since tourists can be assisted especially during the vacation itself. Currently, there is a proliferation of such mobile tourist guides, proposing an unmanageable number of diverse functionalities. To counteract this situation, the contribution of this paper is threefold. First, an evaluation framework is proposed, comprising both, a classification of mobile tourist services and a categorization of their delivery aspects in terms of several orthogonal dimensions. Second, on basis of this framework, four representative mobile tourist guides are evaluated, thereby demonstrating the frameworks' applicability. Third, several lessons learned are discussed, thereby shedding light on the current state of effort in the area of mobile tourist
Applications for Proximity Sensors in Music and Sound Performance
Authors: Ben P. Challis, Kate Challis
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

A low cost accessible sound and music control system is described (the Benemin). The interface employs an array of infrared distance measuring sensors that can be mapped to either MIDI pitches or MIDI control messages. When mapped to pitch, a user can interact with the system directly as a musical instrument. When mapped to controller messages, the system can be used as a multiparametric sound-controller. The Benemin has been designed to be inclusive such that it is aimed at users with or without specific needs. A model for testing is presented along with an indication of preliminary results.