ppxscal/embedding_network huggingface dataset:
Autonomous Index Optimization in XML Databases
Authors: Beda Christoph Hammerschmidt, Martin Kempa, Volker Linnemann
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Defining suitable indexes is a major task when optimizing a database. Usually, a human database administrator defines a set of indexes in the design phase of the database. This can be done manually or with the help of so called index wizard tools analyzing predefined database operations. Even having an optimal initial set of indexes when setting up a database, there is no guarantee that these indexes will suit future demands. Rather, it is realistic that the typical usage of the database will change after a while because new queries appear, for instance. In consequence, the existing indexes are suboptimal. The typical way to handle this problem is that a database administrator maintains the database permanently. In XML database management systems (XDBMS) this problem becomes even worse: Because XML queries cover both content and structure the number of possible queries and indexes is significantly higher. Additionally, for XML data without schema information, queries and indexes cannot be defined in advance, because the structure and the content of the data is not restricted. Both facts tend to result in higher maintenance costs for XML indexes compared to relational indexes. In this paper we show by performance measurements that an adaptive XDBMS that analyzes its workload periodically and creates/drops XML indexes automatically guarantees a high performance over the total life time of a database. Although we present our index system called KeyX the idea and the results are transferable to other XML indexing approaches.
Prototype application with electromyogram interface in immersive virtual environment
Authors: Hideaki Touyama, Koichi Hirota, Michitaka Hirose
Venue: Proceedings of the 2005 international conference on Augmented tele-existence (2005)

We make a report on implementation of electromyogram (EMG) interface in CAVE-clone immersive multiscreen display and propose the advantages. We measured EMG signals and obtained high signal-to-noise (SN) ratio in CABIN immersive virtual environment at the University of Tokyo. The observed SN ratio could make EMG signals a reliable input channel, and real time control of virtual objects was successfully performed. The additional bio-channel reflects the degree of activation of the user's muscles to realize complex and fine operations even with definite motions.
CoCoA: Coordinated Cooperative Localization for Mobile Multi-Robot Ad Hoc Networks
Authors: Dimitrios Koutsonikolas, Saumitra M. Das, Y. Charlie Hu, Yung-Hsiang Lu, C. S. George Lee
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

Mobile robot teams are particularly suited to applications where infrastructure is unavailable or damaged since they can be used to quickly form an infrastructure-less mobile ad hoc network performing tasks in a distributed manner. In such deployment scenarios, localization of individual robots is essential for enabling many applications. In this paper, we propose CoCoA, Coordinated Cooperative localization for mobile multi-robot Ad Hoc Networks, that is low-cost, quickly deployable, energy-efficient, and provides reasonable accuracy for the applications. In CoCoA, only a subset of the robots in the mobile robot team are equipped with external localization devices (e.g. GPS, laser rangers, vision sensors). Subsequently, while robots perform their tasks, they cooperate to help localize each other without requiring static landmarks to be deployed. In addition, CoCoA coordinates the localization operations of robots to reduce energy consumption. Using detailed simulations and localization models calibrated from experimental data, we find that CoCoA is effective in reducing energy consumption while providing good localization accuracy.
Consumer Modelling in Support of Interface Design
Authors: Timothy J. Maciag, Dominik Slezak, Daryl H. Hepting
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

There is significant interest in developing new methods to design more effective user interfaces for decision support tools in online shopping environments. Many online companies have already begun to provide their consumers with enhanced user interface options, such as the ability to customize and/or personalize their user interface. However, for these enhanced options to produce meaningful, useful results, consumers are often required to input substantial amounts of information, placing a strain on the consumers' cognitive decision-making abilities and disrupting their focus on their immediate decision task(s). In this paper, the authors describe a personalization technique to reduce the amount of consumer information required to develop and deploy systems providing these enhanced options. Over the course of the three experiments, the authors built upon each experiment utilizing a combination of traditional statistical methods and rough set theory. This paper will describe the refined technique and the procedures, algorithms, observations, and analysis of the experiments conducted. As well, a discussion detailing future work will be provided.
Direct Evidence for a Binding between Cognitive and Motor Functions in Humans: A TMS Study
Authors: Mireille Bonnard, Mickael Camus, Jozina De Graaf, Jean Pailhous
Venue: Journal of Cognitive Neuroscience (2003)

During voluntary motor actions, the cortico-spinal (CS) excitability is known to be modulated, on the one hand by cognitive (intention-related) processes and, on the other hand, by motor (performance-related) processes. Here, we studied the way these processes interact in the tuning of CS excitability during voluntary wrist movement. We used transcranial magnetic stimulation (TMS) both as a reliable tool for quantifying the CS excitability, through the motor-evoked potentials (MEPs), and as a central perturbation evoking a movement (because the stimulation intensity was above threshold) with subjects instructed to prepare (without changing their muscle activation) either to "let go" or to "resist" to this evoked movement. We studied the simultaneous evolution of both the motor performance and the MEPs in the wrist flexor and extensor, separately for the successful trials (on average, 66% of the trials whatever the condition) and the unsuccessful trials; this allowed us to dissociate the intention- and performance-related processes. To their great surprise, subjects were found able to cognitively prepare themselves to resist a TMS-induced central perturbation; they all reported an important cognitive effort on the evoked movement. Moreover, because TMS only evoked short-latency MEPs (and no long-latency components), the amplitude of these short-latency MEPs was found to be related in a continuous way to the actual movement whatever the prior intention. These results demonstrate that prior intention allows an anticipatory modulation of the CS excitability, which is not only selective (as already known) but also efficient, giving the intended motor behavior a real chance to be realized. This constitutes a direct evidence of the role of the CS excitability in the binding between cognitive and motor processes in humans.
On generic method models
Authors: Naveen Prakash
Venue: Requirements Engineering (2006)

The generic method model assumes that methods abound and method engineering and application engineering is done in diverse areas. Therefore, it is necessary to understand the notion of a method independent of information systems and software engineering. The generic model presented here abstracts out from product and process meta-models to define a system of concepts that can be used in any domain. Additionally, it integrates in it essential features of methods like quality checking, guidance, backtracking, and traceability. The proposed generic model looks upon a method in two parts, the static and the dynamic parts. The former provides the basic structure of a method whereas the latter is the enactment support provided for application development. The static part provides the notion of method blocks and dependencies between them. Method blocks can be enacted. The generic model is a triple <M, D, E> where M is the set of method blocks, D is the set of dependencies between method blocks, and E is the enactment mechanism.
Event-Related Potential Correlates of the Retrieval of Emotional and Nonemotional Context
Authors: Adam P.R. Smith, Raymond J. Dolan, Michael D. Rugg
Venue: Journal of Cognitive Neuroscience (2004)

In two experiments, we examined event-related potentials (ERPs) elicited in an old/new recognition memory test by emotionally neutral visual objects that, at encoding, had been associated with neutrally, negatively, or positively valenced background contexts. In Experiment 2, subjects also judged the context in which the item had been studied. In Experiment 1, ''left parietal'' old/new ERP effects were elicited by correctly recognized items. Items encoded in emotional contexts, but not those studied in neutral contexts, elicited additional effects early in the recording epoch over lateral temporal scalp and, later, over left temporo-frontal scalp. In Experiment 2, ''left parietal'' and ''right frontal'' ERP effects were elicited by recognized items that attracted correct source judgments. Additional effects, an early lateral temporal positivity and a late-onset, left-sided positivity, were elicited by items studied in emotionally valenced contexts and attracting correct source judgments. Together, the findings indicate that retrieval processing is influenced by the emotional valence of the context in which an item is encoded, regardless of whether contextual information is task relevant.
TETE: A Non-Invasive Unit Testing Framework for Source Transformation
Authors: Derek M. Shimozawa, James R. Cordy
Venue: Proceedings of the 13th IEEE International Workshop on Software Technology and Engineering Practice (2005)

While the use of test-driven development as a debugging, pedagogic, and analytical methodology for objectoriented and procedural systems is well documented, it is a relatively unexplored and informal practice within the paradigm of source transformation. This paper describes a test-driven approach to the specification and evaluation of source transformation programs through rule-by-rule and type-by-type unit testing. We introduce the Transformation Engineering Toolkit for Eclipse (TETE), a test-driven framework centered around a simple yet flexible infrastructure for automatically and non-invasively unit testing subtransformations, application strategies, and grammar types specified in the TXL source transformation language.
Flooding strategy for target discovery in wireless networks
Authors: Zhao Cheng, Wendi B. Heinzelman
Venue: Wireless Networks (2005)

In this paper, we address a fundamental problem concerning the best flooding strategy to minimize cost and latency for target discovery in wireless networks. Should we flood the network only once to search for the target, or should we apply a so-called "expansion ring" mechanism to reduce the cost? If the "expansion ring" mechanism is better in terms of the average cost, how many rings should there be and what should be the radius of each ring? We separate wireless networks based on network scale and explore these questions. We prove that two-ring and three-ring schemes can reduce the cost of flooding compared to a single attempt, and we provide a general formula to determine good parameters for the two-ring and three-ring hop-based flooding schemes. Through simulations, we show that choosing flooding parameters according to our techniques gives performance close to that of ideal flooding schemes. Afterwards, we extend our work from the single target discovery problem to the multi-target discovery problem. We show that a properly chosen searching radius can save much more searching cost than a simple radius selection scheme for multi-target discovery problems.
Dimensionality reduction in patch-signature based protein structure matching
Authors: Zi Huang, Xiaofang Zhou, Dawei Song, Peter Bruza
Venue: Proceedings of the 17th Australasian Database Conference - Volume 49 (2006)

Searching bio-chemical structures is becoming an important application domain of information retrieval. This paper introduces a protein structure matching problem and formulates it as an information retrieval problem. We first present a novel vector representation for protein structures, in which a protein structural region, formed by the vectors within the region, is defined as a patch and indexed by its patch signature. For a k-sized patch, its patch signature consists of 7k - 10 inter-atom distances which uniquely determine the patch's spatial structure. A patch matching function is then defined. As structures for proteins are large and complex, it is computationally expensive to identify possible matching patches for a given protein against a large protein database. We propose to apply dimensionality reduction to the patch signatures and show how the two problems are adapted to fit each other. The Locality Preservation Projection (LPP) and Singular Value Decomposition (SVD) are chosen and tested for this purpose. Experimental results show that the dimensionality reduction improves the searching speed while maintaining acceptable precision and recall. From a more general point of view, this paper demonstrates that information retrieval techniques can play a crucial role in solving this biologically critical but computationally expensive problem.
Shape Retrieval Using Matching Pursuit Decomposition
Authors: Binhai Wang, J. Andrew Bangham
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

This paper presents an approach of shape retrieval using linear regression. This approach extracts object edges from decomposed images in different scale levels and approximates them by the linear regression algorithm Matching Pursuit (MP). MP uses linear combination of circular Gaussian basis functions to reconstruct target edges. Each Gaussian basis function contains several features: scale, position and amplitude, which are used to compute distance of two contours. Shapes are retrieved according to the distances between query image and all images in a database.
A Framework for Online Semantic Adaptation of Scalable Video
Authors: Luis Herranz
Venue: Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization (2006)

Scalable video coding and content-based adaptation have become key technologies to adapt content to diverse constrained usage environments (such as PDAs, mobile phones and networks,), while keeping its semantics. In this paper is proposed a framework where the adaptation of scalable video is guided by some semantics in the content. Specifically, an adaptive skimming scheme guided by content activity and its use for fast browsing of sequences are described. Efficiency is achieved computing activity using compressed domain analysis. Several metrics are evaluated as measures of activity.
A complete and decidable security-specialised logic and its application to the TESLA protocol
Authors: Alessio Lomuscio, Bozena Woźna
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

We examine a logic to reason about security protocols by means of temporal and epistemic concepts. We report results on completeness and decidability of the formalism as well as its expressiveness. As a case study we apply the formalism in the analysis of TESLA, a secure stream multi-cast protocol.
A Network-aware Scalable Video Congestion Control Mechanism in Heterogeneous Wireless Networks
Authors: Yinglei Fan, Fang Su, Yong Li, Huimin Xu
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2006)

Providing quality-of-service (QoS) for video delivery in heterogeneous wireless networks is a challenging problem. To have QoS provision at application level, effective congestion control is very necessary. We investigate this problem and present a network-aware scalable video congestion control mechanism in heterogeneous wireless networks. The mechanism not only adapts to the dynamical network condition, but also improves the perceived visual QoS. In this control mechanism, first, each layer of the scalable video is given different protection in terms of packet loss and delay. Secondly, we monitor or model the bottle link to estimate the available network bandwidth dynamically. Thirdly, the QoS mapping module translates the QoS exponents to the effective capacity according to the effective capacity theory. Lastly, the congestion control mechanism adjusts the scalable video according to the compare result between the estimated bandwidth and the requested effective capacity. Finally, simulation results demonstrate effectiveness of our congestion control mechanism.
Building Models of Animals from Video
Authors: Deva Ramanan, David A. Forsyth, Kobus Barnard
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

This paper argues that tracking, object detection, and model building are all similar activities. We describe a fully automatic system that builds 2D articulated models known as pictorial structures from videos of animals. The learned model can be used to detect the animal in the original video—in this sense, the system can be viewed as a generalized tracker (one that is capable of modeling objects while tracking them). The learned model can be matched to a visual library; here, the system can be viewed as a video recognition algorithm. The learned model can also be used to detect the animal in novel images—in this case, the system can be seen as a method for learning models for object recognition. We find that we can significantly improve the pictorial structures by augmenting them with a discriminative texture model learned from a texture library. We develop a novel texture descriptor that outperforms the state-of-the-art for animal textures. We demonstrate the entire system on real video sequences of three different animals. We show that we can automatically track and identify the given animal. We use the learned models to recognize animals from two data sets; images taken by professional photographers from the Corel collection, and assorted images from the Web returned by Google. We demonstrate quite good performance on both data sets. Comparing our results with simple baselines, we show that, for the Google set, we can detect, localize, and recover part articulations from a collection demonstrably hard for object recognition.
A construction of arrays free of rank ambiguities
Authors: Kah-Chye Tan, Zenton Goh
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Schmidt [1981] has established that ambiguity in steering vectors would lead to ambiguous direction-of-arrival (DOA) estimates. In the literature, arrays free of upto rank-k ambiguities, where k/spl ges/3, have not been identified. The present authors construct a class of cross arrays which are free of upto rank-k ambiguities, where k/spl isin/{1, 2...}. Through the study, they derive a theorem for characterizing inherent ambiguities associated with a class of cross and circular arrays. They also provide a counterexample to the conjecture for characterizing higher rank ambiguity, proposed by Lo and Marple [1992].
Groupwise point pattern registration using a novel CDF-based Jensen-Shannon Divergence
Authors: Fei Wang, Baba C. Vemuri, Anand Rangarajan
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

In this paper, we propose a novel and robust algorithm for the groupwise non-rigid registration of multiple unlabeled point-sets with no bias toward any of the given pointsets. To quantify the divergence between multiple probability distributions each estimated from the given point sets, we develop a novel measure based on their cumulative distribution functions that we dub the CDF-JS divergence. The measure parallels the well known Jensen-Shannon divergence (defined for probability density functions) but is more regular than the JS divergence since its definition is based on CDFs as opposed to density functions. As a consequence, CDF-JS is more immune to noise and statistically more robust than the JS. We derive the analytic gradient of the CDF-JS divergence with respect to the non-rigid registration parameters for use in the numerical optimization of the groupwise registration leading a computationally efficient and accurate algorithm. The CDF-JS is symmetric and has no bias toward any of the given point-sets, since there is NO fixed reference data set. Instead, the groupwise registration takes place between the input data sets and an evolving target dubbed the pooled model. This target evolves to a fully registered pooled data set when the CDF-JS defined over this pooled data is minimized. Our algorithm is especially useful for creating atlases of various shapes (represented as point distribution models) as well as for simultaneously registering 3D range data sets without establishing any correspondence. We present experimental results on non-rigid registration of 2D/3D real point set data.
Supervised classification for video shot segmentation
Authors: Yanjun Qi, A. Hauptmann, Ting Liu
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

In this paper, we explore supervised classification methods for video shot segmentation. We transform the temporal segmentation problem into a multi-class categorization issue. This approach provides a uniform framework for using different kinds of features extracted from the video and for detecting various types of shot boundaries. The approach utilizes manual labeled training data and a simple classification structure, which eliminates arbitrary thresholds and achieves more reliable estimation than previous threshold-based methods. Contrastive experiments on 13 videos (/spl sim/4 hours) show excellent performance on the 2001 TREC video track shot classification task in terms of precision and recall.
An introduction to ROC analysis
Authors: Tom Fawcett
Venue: Pattern Recognition Letters (2006)

Receiver operating characteristics (ROC) graphs are useful for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been used increasingly in machine learning and data mining research. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls when using them in practice. The purpose of this article is to serve as an introduction to ROC graphs and as a guide for using them in research.