ppxscal/embedding_network huggingface dataset:
Facilitating Universal Multimedia Adaptation (UMA) in a Heterogeneous Peer-to-Peer Network
Authors: Letian Rong, Ian Burnett
Venue: Proceedings of the Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (2006)

This paper proposes a P2P architecture which uses MPEG-21 as a standard based technique to dynamically adapt resources according to various usage environment attributes such as terminal capabilities and user preferences. In the architecture, a super peer based approach is used to cluster peers, store peer information, perform searches and instruct peers to adapt/send resources. Pull and push-based adaptation methods are introduced to adapt search results and resources in an intelligent manner based on the usage environment attributes. Simulation results show that the proposed architecture reduces download time while increasing resource availabilities and download speed in the network when compared to traditional P2P systems.
A New Text Categorization Technique Using Distributional Clustering and Learning Logic
Authors: Hisham Al-Mubaid, Syed A. Umair
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

Text categorization is continuing to be one of the most researched NLP problems due to the ever-increasing amounts of electronic documents and digital libraries. In this paper, we present a new text categorization method that combines the distributional clustering of words and a learning logic technique, called Lsquare, for constructing text classifiers. The high dimensionality of text in a document has not been fruitful for the task of categorization, for which reason, feature clustering has been proven to be an ideal alternative to feature selection for reducing the dimensionality. We, therefore, use distributional clustering method (IB) to generate an efficient representation of documents and apply Lsquare for training text classifiers. The method was extensively tested and evaluated. The proposed method achieves higher or comparable classification accuracy and {\rm F}_1 results compared with SVM on exact experimental settings with a small number of training documents on three benchmark data sets WebKB, 20Newsgroup, and Reuters-21578. The results prove that the method is a good choice for applications with a limited amount of labeled training data. We also demonstrate the effect of changing training size on the classification performance of the learners.
Coordinating simple and unreliable agents
Authors: Kagan Tumer
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Coordinating a large number of simple and unreliable agents to achieve a global objective poses a unique design challenge: How to achieve robust system level behavior in spite of the computational/reliability limitations of the agents. We investigate agent coordination in the difficult optimization problem of selecting the subset of sensing devices with distortions that provides the smallest average distortion [1]. We approach problem by assigning an agent to each device and having that agent use a simple reinforcement learning algorithm to determine whether to be part of the aggregate device. Our results show that the right agent reward structure provides significant improvements over both traditional search methods and traditional multi-agent methods. Furthermore, even in extreme cases of agent failures (i.e., half the agents fail during the simulation) this approach still outperforms a failure-free and centralized search algorithm.
Challenges and benefits of time-parallel simulation of wireless ad hoc networks
Authors: Ladislau Bölöni, Damla Turgut, Guoqiang Wang, Dan C. Marinescu
Venue: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools (2006)

In this paper we discuss time-parallel simulation of wireless ad hoc networks. Such systems are rarely amenable to analytical modelling due to the complexity of the models involved. Thus, to obtain a quantitative evaluation of such models we often resort to simulation. Yet, current simulation techniques do not allow us to study systems consisting of thousands of nodes for extended periods of time.We introduce the notion of perturbation of measurements and present a layer-by-layer analysis of the impact of perturbations on the functioning of the wireless network. This model allows us to predict the accuracy of the simulation for several measures of performance through an analysis of the protocols involved at the various layers.We also present an implementation of time-parallel simulation based on iterative extension of the warmup period. In a series of experiments, we find good concordance between the predicted findings and the results of the simulations.
Exploiting Author-Designed Domain-Specific Descriptive Markup Languages in the Production of Learning Content
Authors: Jose L. Sierra, Alfredo Fernandez-Valmayor, Mercedes Guinea
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

In this paper we describe an approach to the production of learning resources where authors (students and instructors) are actively involved in the production process. This active involvement is achieved by using descriptive markup technologies. Authors are compelled to produce learning resources in the form of documents, and to make the structure of these documents explicit by creating and using descriptive markup languages. This lets developers formalize these author-designed markup languages and provide suitable transformation specifications for translating these marked documents into their final presentations. We exemplify this approach with the production of DHTML pages by Ph.D. students in archaeology, oriented to be used as resources owned by reusable learning objects in Chasqui, an authoring and deployment tool used in the virtualization of academic museums at the Complutense University of Madrid (Spain).
Enhancing simulation education with a virtual presentation tool
Authors: David He, Pat Banerjee
Venue: Proceedings of the 36th conference on Winter simulation (2004)

This paper describes a research plan to address the undergraduate learning challenges encountered when teaching an introductory simulation course in Industrial Engineering programs. It outlines the implementation tasks of the research methodology, an evaluation plan, and one direction for future work.
A Multi-Objective Evolutionary Algorithm to Build Knowledge Classification Rules with Specific Properties
Authors: Adriano D. Pila, Rafael Giusti, Ronaldo C. Prati, Maria Carolina Monard
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

This work proposes the use of evolutionary algorithms to build individual knowledge rules with specific properties that are usually neglected when conducted by traditional supervised learning methods. The proposed evolutionary algorithm uses a rank-based, multi-objective fitness function that enables the arrangement of any set of measures. Experimental results that show the suitability of our proposal are also presented.
On past-time indexing of moving objects
Authors: Katerina Raptopoulou, Michael Vassilakopoulos, Yannis Manolopoulos
Venue: Journal of Systems and Software (2006)

Tracking of mobile objects trajectories is one of many modern applications supported by Spatiotemporal databases. Within the context of this application, queries about the present, future or past positions of the objects need to be answered. Several indexing methods have been proposed to efficiently handle such spatiotemporal queries. In the current paper, we propose a method for indexing the historic (past) positions of moving objects called XBR-tree, a quadtree-like technique that is able to handle both timestamp and window queries. Moreover, we compare experimentally this with other methods proposed in the literature for the same purpose. In particular, we compare XBR-trees with PMR-trees, structures also related to quadtrees and MV3R-trees, R-tree based structures.
Wavelet-based phase classification
Authors: Ted Huffmire, Tim Sherwood
Venue: Proceedings of the 15th international conference on Parallel architectures and compilation techniques (2006)

Phase analysis has proven to be a useful method of summarizing the time-varying behavior of programs, with uses ranging from reducing simulation time to guiding run-time optimizations. Although phase classification techniques based on basic block vectors have shown impressive accuracies on SPEC benchmarks, commercial programs remain a significant challenge due to their complex behaviors and multiple threads. Some behaviors, such as L2 cache misses, may have less correlation with the code and therefore are much harder to capture with basic block frequency vectors.Comparing the similarity of two or more intervals requires a good metric, one that is not only fast enough to analyze the full execution of the program, but that is also highly correlated with important performance degrading events (such as L2 misses). We examine the use of many different interval similarity metrics and their uses for program phase analysis across a range of commercial applications and show that there is still significant room for improvement. To address this problem, we introduce a novel wavelet-based phase classification scheme that captures and compares images of memory behavior in two or more dimensions. Over a set of five commercial applications, we show that a wavelet-based scheme can strictly outperform a broad range of prior metrics both in terms of accuracy and overhead.
Concept for Audio Quality and Security Assurance in Mobile Phones as Multimodal User Guides
Authors: Andrea Oermann, Sandra Gebbensleben, Claus Vielhauer, Jana Dittmann
Venue: Proceedings of the Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (2006)

This paper presents a new concept of an approach to evaluate the assurance of the audio quality and its impact on the security of mobile phones used as multimodal user guides at the same time. Differently caused interferences can influence the subjectively perceived audio signal. Finding objective measure values acts as the motivation for the development of the presented model. This model to evaluate audio codecs in relation to three defined and interdependent challenges, addressing three different kinds of problems -- technical, environmental, and security, will be introduced while its evaluation is in progress. As a result, our model, which is still work in process, will help to provide recommendations to future developments and to establish standardizations in the field of multimodal user guides.
Autonomous agents for air-traffic deconfliction
Authors: Michal Pěchouček, David Šišlák, Dušan Pavlíček, Miroslav Uller
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

This contribution presents a deployment exercise of multi-agent technology in the domain of deconflicted air-traffic control among several autonomous aerial vehicles (manned as well as unmanned). Negotiation based deconfliction algorithm have been developed and integrated in the agent-based model of the individual flight. Operation of the underlying multi-agent system has been integrated with freely available, geographical and tactical data sources in order to demonstrate openness of the technology. An additional, web client visualization and access component has been developed in order to facilitate a multi-user, platform independent use of the system. The features and application design is illustrated in the demonstration video clip.
Frequent Closed Itemset Mining Using Prefix Graphs with an Efficient Flow-Based Pruning Strategy
Authors: H. D. K. Moonesinghe, Samah Fodeh, Pang-Ning Tan
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

This paper presents PGMiner, a novel graph-based algorithm for mining frequent closed itemsets. Our approach consists of constructing a prefix graph structure and decomposing the database to variable length bit vectors, which are assigned to nodes of the graph. The main advantage of this representation is that the bit vectors at each node are relatively shorter than those produced by existing vertical mining methods. This facilitates fast frequency counting of itemsets via intersection operations. We also devise several internode and intra-node pruning strategies to substantially reduce the combinatorial search space. Unlike other existing approaches, we do not need to store in memory the entire set of closed itemsets that have been mined so far in order to check whether a candidate itemset is closed. This dramatically reduces the memory usage of our algorithm, especially for low support thresholds. Our experiments using synthetic and real-world data sets show that PGMiner outperforms existing mining algorithms by as much as an order of magnitude and is scalable to very large databases.
Source selectable path diversity via routing deflections
Authors: Xiaowei Yang, David Wetherall
Venue: Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications (2006)

We present the design of a routing system in which end-systems set tags to select non-shortest path routes as an alternative to explicit source routes. Routers collectively generate these routes by using tags as hints to independently deflect packets to neighbors that lie off the shortest-path. We show how this can be done simply, by local extensions of the shortest path machinery, and safely, so that loops are provably not formed. The result is to provide end-systems with a high-level of path diversity that allows them to bypass unde-sirable locations within the network. Unlike explicit source routing, our scheme is inherently scalable and compatible with ISP policies because it derives from the deployed Internet routing. We also sug-gest an encoding that is compatible with common IP usage, making our scheme incrementally deployable at the granularity of individual routers.
Partition-based adaptive estimation of single response evoked potentials
Authors: A. M. Sarhan, R. C. Hardie, K. E. Barner
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

We have introduced and analyzed a new class of adaptive nonlinear filters referred to as partition-based linear (Pl) filters. The operation of those filters depends on partitioning the observation space in some fashion. Specifically, we have used here scaler quantization as an example to illustrate the concept of partitioning the observation space. Each partition is then assigned an output based on linear combinations of observed samples in a moving window of finite length N. The filters are shown to exhibit appealing robustness. Simulations include a novel approach to estimating response-to-response variations in evoked potentials (EP), buried in the on-going electroencephalogram (EEG). Unlike the multi-channel filters currently used in EP estimation, the Pl filters do not require a separate electrode to provide a reference signal. In addition, no repetition of the stimulus is needed and the time of the stimulus need not be known.
Modeling a web-based remote monitoring and fault diagnosis system with UML and component technology
Authors: Xing Wu, Jin Chen, Ruqiang Li, Weixiang Sun, Guicai Zhang, Fucai Li
Venue: Journal of Intelligent Information Systems (2006)

As the Machinery Condition Monitoring and Fault Diagnosis Systems (MCMFDSs) are more and more complex, the design and development of these systems are becoming a challenge. The best way to manage the complexity and risk is to abstract and model them. This paper presents a new method of modeling Web-based Remote Monitoring and Fault Diagnosis Systems (WRMFDSs) with Unified Modeling Language (UML). A component framework model is put forward. A highly maintainable WRMFDS with three reusable component packages was developed using component-based programming. This paper, which studies a reusable WRMFDS model, aims at making such advanced information technologies be used widely in the condition monitoring and fault diagnosis domain, it can give developers a paradigm to accomplish the similar systems.
Teaching Agile - Agile Teaching: Creating a Holistic Learning Environment
Authors: Fred Grossman, Joe Bergin, Rinaldo DiGiorgio
Venue: Proceedings of the conference on AGILE 2006 (2006)

This workshop brings together educators, trainers and students with an interest in teaching Agile principles and practices in an agile way. We will take a holistic approach to courses and curricula to gather advice on effective teaching environments and techniques for agile topics.
Multiclass SVM Design and Parameter Selection with Genetic Algorithms
Authors: Ana Carolina Lorena, Andre C. P. L. F. de Carvalho
Venue: Proceedings of the Ninth Brazilian Symposium on Neural Networks (2006)

Support Vector Machines (SVMs) are originally designed for the solution of two-class problems. In multiclass applications, several strategies divide the original problem into binary subtasks, whose results are combined. In a previous work, Genetic Algorithms were used to determine the combination of binary SVMs in a multiclass solution. In order to improve the classification performance obtained, this algorithm was extended to search the parameter values of the binary SVMs contained in the decompositions. This paper presents results of the proposed algorithm in four datasets, with encouraging results.
Proceedings of the 2006 ACM SIGPLAN workshop on Generic programming
Venue: International Conference on Functional Programming (2006)

It is my great pleasure to welcome you to the ACM SIGPLAN Workshop on Generic Programming 2006 -- WGP 2006, held in Portland, Oregon, US, on 16th September 2006. The workshop is sponsored by ACM SIGPLAN and is affiliated with the 11th ACM SIGPLAN International Conference on Functional Programming (ICFP 2006). Previous Workshops on Generic Programming have been held in Marstrand (affiliated with MPC), Ponte de Lima (affiliated with MPC), Nottingham (informal workshop), Dagstuhl (IFIP WG2.1 Working Conference), Oxford (informal workshop), and Utrecht (informal workshop).The call for papers generated 20 submissions from Asia, Canada, Europe, Africa, and the United States. Each paper was evaluated by at least three members of the programme committee with the help of several additional reviewers. During a five-day virtual meeting, the programme committee selected 10 papers for presentation at the workshop. The papers cover a variety of topics, including design patterns, type systems and implementations of generic programming. I hope that the proceedings will serve as a valuable reference for both researchers and students.
IO-Top-k: index-access optimized top-k query processing
Authors: Holger Bast, Debapriyo Majumdar, Ralf Schenkel, Martin Theobald, Gerhard Weikum
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

Top-k query processing is an important building block for ranked retrieval, with applications ranging from text and data integration to distributed aggregation of network logs and sensor data. Top-k queries operate on index lists for a query's elementary conditions and aggregate scores for result candidates. One of the best implementation methods in this setting is the family of threshold algorithms, which aim to terminate the index scans as early as possible based on lower and upper bounds for the final scores of result candidates. This procedure performs sequential disk accesses for sorted index scans, but also has the option of performing random accesses to resolve score uncertainty. This entails scheduling for the two kinds of accesses: 1) the prioritization of different index lists in the sequential accesses, and 2) the decision on when to perform random accesses and for which candidates.The prior literature has studied some of these scheduling issues, but only for each of the two access types in isolation. The current paper takes an integrated view of the scheduling issues and develops novel strategies that outperform prior proposals by a large margin. Our main contributions are new, principled, scheduling methods based on a Knapsack-related optimization for sequential accesses and a cost model for random accesses. The methods can be further boosted by harnessing probabilistic estimators for scores, selectivities, and index list correlations. In performance experiments with three different datasets (TREC Terabyte, HTTP server logs, and IMDB), our methods achieved significant performance gains compared to the best previously known methods.
An Improved Handover Method Using Mobile Tracking on Telematics
Authors: Seong-Yoon Shin, Jong-Chan Lee, Yang-Won Rhee
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01 (2006)

It is widely accepted that the coverage with high user densities can only be achieved with small cell such as micro- and pico-cell. The smaller cell size causes frequent handovers between cells and a decrease in the permissible handover processing delay. This may result in the handover failure, in addition to the loss of some packets during the handover. In these cases, re-transmission is needed in order to compensate errors, which triggers a rapid degradation of throughput. In this paper, we propose a new handover scheme in the next generation mobile communication systems, in which the handover setup process is done in advance before a handover request by predicting the handover cell based on mobile terminal's current position and moving direction. Simulation is focused on the handover failure rate and packet loss rate. The simulation results show that our proposed method provides a better performance than the conventional method.
An internet system of partner-learning special type
Authors: N. A. Poroshin, O. P. Skljarov
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

An Internet system for stuttering, correction based upon so-called partner principles is offered In the system as a trainee as a learning models are Feigenbaum scenario of route to chaos for dynamical regimes of trainee's speech rhythm as result of both learning and/or an external feedback of various type. In the paper dynamics of speech rate and rhythm is traced during its self-correction by trainee in accordance with various methods are being developed in the system. It estimates the efficacy of various strategy of self-correction in dependence of deviation of trainee's rate and rhythm from norm. The system allows implementing process of stuttering self-correction. At the same time the various strategies of stuttering correction in dependence of rate and rhythm behavior are detected. This trajectory has conforming to a modification of rate and a rhythm during correction. There are two basic strategies which are known as "pulled speech" and "tunnel passage" methods. Combination of these strategies has allowed increasing efficacy of stuttering correction. The outcomes are interpreted in the terms of response-contingent feedback reacting in Hopfield network. Both strategies are explained with the theory of rhythm dynamic regimes control within Feigenbaum scenario.
Contributions of Subregions of the Prefrontal Cortex to Working Memory: Evidence from Brain Lesions in Humans
Authors: Notger G. Müller, Liana Machado, Robert T. Knight
Venue: Journal of Cognitive Neuroscience (2002)

We investigated working memory in patients with focal brain damage involving subregions of the prefrontal cortex (PFC). Lesions in the dorsal portion of lateral PFC or the ventromedial portion of orbital PFC did not impair performance in tasks that required maintenance and monitoring of object or spatial information. Larger lesions involving both ventral and dorsal parts of the lateral PFC impaired maintenance and monitoring of spatial and object information, with more severe deficits observed in the spatial tasks. The results support a distributed localization of function in lateral PFC during working memory.