ppxscal/embedding_network huggingface dataset:
Controlling Uncertainty in Personal Positioning at Minimal Measurement Cost
Authors: Hui Fang, Wen-Jing Hsu, Larry Rudolph
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

One interesting scenario in personal positioning involves an energy-conscious mobile user who tries to obtain estimates about his positions with sufficiently high confidence while consuming as little battery energy as possible. Besides obtaining estimates directly from a position measuring device, the user can rely on extrapolative calculations based on a user movement model and a known initial estimate. Because each measuring probe usually incurs a substantially higher cost than the extrapolative calculation, the objective is to minimize the overall cost of the measurement probes.Assuming that the user moves at a normally-distributed velocity, we consider two scenarios which differ in the probing devices used. In the first scenario, only one probing device is used. In this case, the aim is to minimize the total number of probes required. In the second scenario, two types of positioning devices are given, where one type of devices offers a higher positioning precision, but also at a greater probing cost. In this case, the aim is to choose an optimal combination of probes from the two types of devices.For both scenarios, we present algorithms for determining the minimum-cost probing sequences. The algorithms are computationally efficient in reducing the searching space of all possible probing sequences. Our approach is based on Kalman Filtering theory which allows to integrate estimates obtained from the measurements and the extrapolative calculations. The variances in the estimates can provably stay below the specified level throughout the journey.To the best of our knowledge, these results appear to be the first that uses a mathematically rigorous approach to minimize the probing cost while guaranteeing the quality of estimates in personal positioning.
Dynamic asymmetric communication
Authors: Travis Gagie
Venue: Information Processing Letters (2008)

We show how any dynamic instantaneous compression algorithm can be converted to an asymmetric communication protocol, with which a server with high bandwidth can help clients with low bandwidth send it messages. Unlike previous authors, we do not assume the server knows the messages' distribution, and our protocols are the first to use only one round of communication for each message.
Type-2 Fuzzy Neuro System Via Input-to-State-Stability Approach
Authors: Ching-Hung Lee, Yu-Ching Lin
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

This paper proposes the type-2 fuzzy neural network system (type-2 FNN) which combines the advantages of type-2 fuzzy logic systems (FLSs) and neural networks (NNs). For considering the system uncertainties, we use the type-2 FLSs to develop a type-2 FNN system. The previous results of type-1 FNN systems can be extended to a type-2 one. Furthermore, the corresponding learning algorithm is derived by input-to-state-stability (ISS) approach. Nonlinear system identification is presented to illustrate the effectiveness of our approach.
Cloud Theory Based Simulated Annealing Algorithm for Multiple Observers Sitting on Terrain Problem
Authors: Pin Lv, Lin Yuan, Jinfang Zhang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

The problem of Multiple Observers Sitting on Terrain (MOST) is an important part in visibility-based terrain reasoning and many applications can be classified as this problem. Recent developments in this field concentrate on using heuristic algorithm, such as Simulated Annealing algorithm (SA), but it is still difficult because of unacceptable computing time and low solving precision. In this paper, a Cloud theory based Simulated Annealing algorithm (CSA) is introduced involving two innovations. The first is state changing by using X cloud generator which can make the position selection of observer controllable. The second is temperature annealing by using Y cloud generator which can produce approximatively continuous annealing temperature and fit the physical annealing process in nature much better. Theoretical analysis proves that CSA is convergent for MOST problem. Application experiments show that, using CSA for MOST problem, the average time cost decreases by 40%~60% and the average solution accuracy improves by 10% as compared with using SA.
Underwater Passive Location Technology Using Dummy Time-Reversal Mirror
Authors: Xueli Sheng, Xizhong Bao, Junying Hui, Guolong Liang
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

Time reversal (TR) refocuses the incident acoustic field back to the origin of a probe signal regardless of the complexity of the medium. However, the operation of a TR requires a cooperative probe source. This is impossible in passive work mode. In this paper, a dummy time-reversal mirror (DTRM) method is discussed to introduce the concept of time-reversal into underwater passive location. Several ocean acoustics experiments demonstrating the implementation of DTRM have been conducted. The proposed method is useful while at long source-receive ranges, or while object is moving.
Multiple Instance Learning with MultiObjective Genetic Programming for Web Mining
Authors: Amelia Zafra, Eva Lucrecia Gibaja, Sebastián Ventura
Venue: Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems (2008)

This paper introduces a multiobjective grammar based genetic programming algorithm to solve a Web Mining problem from multiple instance perspective. This algorithm, called MOG3P-MI, is evaluated and compared with other available algorithms which extend a well-known neighborhood-based algorithm (k-nearest neighbour algorithm) and with amono objective version of grammar guided genetic programming G3P-MI. Computational experiments show that, the MOG3PMI algorithm obtains the best results, solves problems of k-nearest neighbour algorithms, such as sparsity and scalability, adds comprehensibility and clarity in the knowledge discovery process and overcomes the results of monoobjective version.
On Optimal Solutions for the Bottleneck Tower of Hanoi Problem
Authors: Yefim Dinitz, Shay Solomon
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

We study two aspects of a generalization of the Tower of Hanoi puzzle. In 1981, D. Wood suggested its variant, where a bigger disk may be placed higher than a smaller one if their size difference is less than k. In 1992, D. Poole suggested a natural disk-moving strategy for this problem, but only in 2005, the authors proved it be optimal in the general case. We describe the family of all optimal solutions to this problem and present a closed formula for their number, as a function of the number of disks and k. Besides, we prove a tight bound for the diameter of the configuration graph of the problem suggested by Wood. Finally, we prove that the average length of shortest sequence of moves, over all pairs of initial and final configurations, is the same as the above diameter, up to a constant factor.
On the Robustness of (Semi) Fast Quorum-Based Implementations of Atomic Shared Memory
Authors: Chryssis Georgiou, Nicolas C. Nicolaou, Alexander A. Shvartsman
Venue: Proceedings of the 22nd international symposium on Distributed Computing (2008)

This paper studies a trade-off between fault-tolerance and latency in implementations of atomic read/write objects in message-passing systems. In particular, considering fast or semifast quorum-based implementations, that is, implementations where all or respectively most read and write operations complete in a single communication round-trip, it is shown that such implementations are not robust due to the fact that they necessarily require a quorum system with a common intersection between its quorums.To trade speed for fault-tolerance, the notion of weak-semifast implementations is introduced. Here more than a single complete slow (two round-trip) read operation is allowed for each write operation (semifast implementations allow only one such slow read). A quorum-based algorithm is given next and it is formally shown that it constitutes a weak-semifast implementation of atomic registers. The algorithm uses the notion of Quorum Views to facilitate the characterization of all possible object timestamp distributions that a read operation may witness during its first communication round-trip. Noteworthy is that the algorithm allows fast read operations even if they are concurrent with other read and write operations. Finally, experimental results were gathered by simulating the algorithm using the NS-2 network simulator. The results show that under realistic conditions, less than 13% of read operations are slow, thus the overwhelming majority of operations take a single communication round-trip.
Text Categorization with Semantic Commonsense Knowledge: First Results
Authors: Pawel Majewski, Julian Szymański
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Most text categorization research exploit bag-of-words text representation. However, such representation makes it very hard to capture semantic similarity between text documents that share very little or even no vocabulary. In this paper we present preliminary results obtained with a novel approach that combines well established kernel text classifiers with external contextual commonsense knowledge. We propose a method for computing semantic similarity between words as a result of diffusion process in ConceptNet semantic space. Evaluation on a Reuters dataset show an improvement in precision of classification.
Can theory meet practice?: the case of multi-channel wireless networks
Authors: Nitin Vaidya
Venue: Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization (2008)

This talk will make the circular argument that theory should be motivated by practical experience, and practical testbeds/evaluations should be motivated by theoretical results. I will base the talk partly on our experience in both areas (theory & testbed) in the context of multi-channel wireless networks.
Smoothed hat functions in subdivision
Authors: C. Conti, K. Jetter
Venue: Journal of Computational and Applied Mathematics (2008)

Following the general idea of smoothing through convolution, we discuss schemes for smoothing hat functions on the three-directional and the four-directional mesh. The smoothing masks-which in the four-directional case are matrix masks-have the same support as the refinement mask for the hat functions. Several smoothing schemes are presented, and in some cases the smoothness properties of the smoothed functions are analysed. In particular, the results for the four-directional case follow new and original lines of research.
Riemannian Framework for Estimating Symmetric Positive Definite 4th Order Diffusion Tensors
Authors: Aurobrata Ghosh, Maxime Descoteaux, Rachid Deriche
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

DTI is an important tool to investigate the brain in vivo and non-invasively in spite of its shortcomings in regions of fiber-crossings. HARDI models such as QBI and Higher Order Tensors (HOT) were invented to overcome this shortcoming. HOTs, however, have not been explored extensively even though sophisticated estimation schemes were developed for DTI that guarantee positive diffusivity, such as the Riemannian framework. Positive diffusivity is an important constraint in diffusion MRI since it represents the physical phenomenon of molecular diffusion. It seems apt, to leverage the work done on DTI, to apply the positivity constraint to the HOT model. We, therefore, propose to extend the Riemannian framework from DTI to the space of 4th order diffusion tensors. We also review the existing methods for estimating 4th order diffusion tensors and compare all methods on synthetic, phantom and real datasets extensively to test for robustness and speed. Our contributions for extending the Riemannian framework from DTI to estimating 4th order diffusion tensors guarantees positive diffusivity, is robust, is fast, and can be used to discern multiple fiber directions.
Global trees: a framework for linked data structures on distributed memory parallel systems
Authors: D. Brian Larkins, James Dinan, Sriram Krishnamoorthy, Srinivasan Parthasarathy, Atanas Rountev, P. Sadayappan
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

This paper describes the Global Trees (GT) system that provides a multi-layered interface to a global address space view of distributed tree data structures, while providing scalable performance on distributed memory systems. The Global Trees system utilizes coarse-grained data movement to enhance locality and communication efficiency. We describe the design and implementation of GT, illustrate its use in the context of a gravitational simulation application, and provide experimental results that demonstrate the effectiveness of the approach. The key benefits of using this system include efficient shared-memory style programming of distributed trees, tree-specific optimizations for data access and computation, and the ability to customize many aspects of GT to optimize application performance.
Quotient lenses
Authors: J. Nathan Foster, Alexandre Pilkiewicz, Benjamin C. Pierce
Venue: ACM SIGPLAN Notices (2008)

There are now a number of BIDIRECTIONAL PROGRAMMING LANGUAGES, where every program can be read both as a forward transformation mapping one data structure to another and as a reverse transformation mapping an edited output back to a correspondingly edited input. Besides parsimony - the two related transformations are described by just one expression - such languages are attractive because they promise strong behavioral laws about how the two transformations fit together - e.g., their composition is the identity function. It has repeatedly been observed, however, that such laws are actually a bit too strong: in practice, we do not want them "on the nose," but only up to some equivalence, allowing inessential details, such as whitespace, to be modified after a round trip. Some bidirectional languages loosen their laws in this way, but only for specific, baked-in equivalences. In this work, we propose a general theory of QUOTIENT LENSES - bidirectional transformations that are well behaved modulo equivalence relations controlled by the programmer. Semantically, quotient lenses are a natural refinement of LENSES, which we have studied in previous work. At the level of syntax, we present a rich set of constructs for programming with CANONIZERS and for quotienting lenses by canonizers. We track equivalences explicitly, with the type of every quotient lens specifying the equivalences it respects. We have implemented quotient lenses as a refinement of the bidirectional string processing language Boomerang. We present a number of useful primitive canonizers for strings, and give a simple extension of Boomerang's regular-expression-based type system to statically typecheck quotient lenses. The resulting language is an expressive tool for transforming real-world, ad-hoc data formats. We demonstrate the power of our notation by developing an extended example based on the UniProt genome database format and illustrate the generality of our approach by showing how uses of quotienting in other bidirectional languages can be translated into our notation.
Exploring cultural heritage sites through space and time
Authors: R. G. Laycock, D. Drinkwater, A. M. Day
Venue: Journal on Computing and Cultural Heritage (JOCCH) (2008)

Traveling through a single virtual environment only tells part of the story; a particularly interesting aspect is to illustrate how an area has developed over time. This article presents a unified approach to illustrating four-dimensional data concerning a cultural heritage site. The proposed framework provides a semi-automatic approach to both reconstructing the environment and bringing all the time-dependent models into an intuitive visualization package. For each time period considered for reconstruction, the system requires a set of building footprint maps depicting the layout of the environment plus a few statistics. The statistics govern the construction of three-dimensional building models, allowing each building's architectural style, typical building height, and roof style to be altered. This information is automatically processed and converted into a form that can be visualized. By integrating high quality landmark buildings from laser scanning or interactive modelling packages into the automatically generated scene, the cultural heritage site is realized both in a spatial and temporal context. The visualization is achieved via a 4D navigable movie which is presented using two concrete implementations written using Flash and OpenGL. The OpenGL-based implementation allows a collection of 3DS Max scenes to be automatically visualized requiring only a set of camera paths identified by the user.
Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm
Authors: Stéphan Clémençon, Nicolas Vayatis
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

We consider the extension of standard decision tree methods to the bipartite ranking problem. In ranking, the goal pursued is global: define an order on the whole input space in order to have positive instances on top with maximum probability. The most natural way of ordering all instances consists in projecting the input data x onto the real line using a real-valued scoring function s and the accuracy of the ordering induced by a candidate s is classically measured in terms of the AUC. In the paper, we discuss the design of tree-structured scoring functions obtained by maximizing the AUC criterion. In particular, the connection with recursive piecewise linear approximation of the optimal ROC curve both in the L 1-sense and in the L ¿ -sense is discussed.
Mining Serial Episode Rules with Time Lags over Multiple Data Streams
Authors: Tung-Ying Lee, En Tzu Wang, Arbee L. Chen
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

The problem of discovering episode rules from static databases has been studied for years due to its wide applications in prediction. In this paper, we make the first attempt to study a special episode rule, named serial episode rule with a time lag in an environment of multiple data streams. This rule can be widely used in different applications, such as traffic monitoring over multiple car passing streams in highways. Mining serial episode rules over the data stream environment is a challenge due to the high data arrival rates and the infinite length of the data streams. In this paper, we propose two methods considering different criteria on space utilization and precision to solve the problem by using a prefix tree to summarize the data streams and then traversing the prefix tree to generate the rules. A series of experiments on real data is performed to evaluate the two methods.
Event Representation in Temporal and Geographic Context
Authors: Ryan Shaw, Ray R. Larson
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

Linking digital resources that refer to the same people or places is becoming common. Events are another kind of entity that might be used to link resources in this way. We examine a number of standards for encoding of archival, historical, genealogical, and news information to compare the tools they offer for representing events.
Predictive Labeling with Dependency Pairs Using SAT
Authors: Adam Koprowski, Aart Middeldorp
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

This paper combines predictive labeling with dependency pairs and reports on its implementation. Our starting point is the method of proving termination of rewrite systems using semantic labeling with infinite models in combination with lexicographic path orders. We replace semantic labeling with predictive labeling to weaken the quasi-model constraints and we combine it with dependency pairs (usable rules and argument filtering) to increase the power of the method. Encoding the resulting search problem as a propositional satisfiability problem and calling a state-of-the-art SAT solver yields a powerful technique for proving termination automatically.
Quality-Driven Continuous Adaptiation of ECG Interpretation in a Distributed Surveillance System
Authors: Piotr Augustyniak
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

Principal rules defining the adaptation of ECG interpretation software in a distributed surveillance network are presented in this paper. Thanks to the pervasive access to wireless digital communication services, the intelligent monitoring networks automatically solve difficult medical cases thanks to the auto-adaptation of data interpretation and transmission to the variable patient status and technical constrains. The foundation of this innovative approach is the use of selected diagnostic parameters in a loopback modifying the running interpretive software. The auto adaptive process maximizes the general estimate of patient description quality aggregating the divergence values of particular parameters modulated by the medical relevance factor dependent on the status of patient. Our approach is motivated by the outcomes from the research on human experts behavior, statistics of the procedures reliability and usage as well as tests in a prototype client-server application. The tests yielded very promising results: the convergence of the remotely computed diagnostic outcome was achieved in over 80% of software adaptation attempts. Comparing to the rigid reporting mode, avoiding unnecessary computation extends the autonomy time by 65% and the transmission channel occupation was reduced by 3,1 to 5,6 times. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A Novel Iris Recognition System
Authors: V. C. Subbarayudu, Munaga V. N. K. Prasad
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Iris recognition as an emerging biometric recognition approach and it’s becoming a very active topic in both research and practical applications. The pattern of the human iris differs from person to person, even between monocular twins. This paper proposes a modified iris localization method and normalization method. In the iris localization after invert the iris image edges are detected by using the canny edge detection. The average of the edge points as taken as coarse center of the pupil. Using coarse center of pupil, Circular Hough Transform method is applied to determine the location of the iris boundaries. The normalization is used for converting the circular iris into rectangular form with fixed dimensions. The proposed method is for non-concentric iris. In this paper 2D Log-Gabor Filters are used for feature extraction and hamming distance is used for matching. The experimental result shows the proposed method has an encouraging performance.