ppxscal/embedding_network huggingface dataset:
Object Detection by Keygraph Classification
Authors: Marcelo Hashimoto, Roberto M. Cesar,  Jr.
Venue: Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition (2009)

In this paper, we propose a new approach for keypoint-based object detection. Traditional keypoint-based methods consist of classifying individual points and using pose estimation to discard misclassifications. Since a single point carries no relational features, such methods inherently restrict the usage of structural information. Therefore, the classifier considers mostly appearance-based feature vectors, thus requiring computationally expensive feature extraction or complex probabilistic modelling to achieve satisfactory robustness. In contrast, our approach consists of classifying graphs of keypoints, which incorporates structural information during the classification phase and allows the extraction of simpler feature vectors that are naturally robust. In the present work, 3-vertices graphs have been considered, though the methodology is general and larger order graphs may be adopted. Successful experimental results obtained for real-time object detection in video sequences are reported.
Solving the "Who's Mark Johnson" puzzle: information extraction based cross document coreference
Authors: Jian Huang, Sarah M. Taylor, Jonathan L. Smith, Konstantinos A. Fotiadis, C. Lee Giles
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium (2009)

Cross Document Coreference (CDC) is the problem of resolving the underlying identity of entities across multiple documents and is a major step for document understanding. We develop a framework to efficiently determine the identity of a person based on extracted information, which includes unary properties such as gender and title, as well as binary relationships with other named entities such as co-occurrence and geo-locations. At the heart of our approach is a suite of similarity functions (specialists) for matching relationships and a relational density-based clustering algorithm that delineates name clusters based on pairwise similarity. We demonstrate the effectiveness of our methods on the WePS benchmark datasets and point out future research directions.
Parameter Estimation Using an Adaptive Immune Clone Selection Algorithm
Authors: Zhang Liu, Hesheng Tang, Cunxin Fan
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

A novel Artificial Immune Algorithm, namely Adaptive Immune Clone Selection Algorithm is proposed in this paper for parameter estimation which can be formulated as a multi-modal optimization problem with high dimension. In this method the secondary response, adaptive mutation regulation and vaccination operator are introduced in the generic Clone Selection Algorithm to improve the convergence speed and global optimum searching ability. Simulation results for identifying the parameters of a dynamic system are presented to demonstrate the effectiveness of the proposed method.
Hiding Information by Context-Based Synonym Substitution
Authors: Xueling Zheng, Liusheng Huang, Zhili Chen, Zhenshan Yu, Wei Yang
Venue: Proceedings of the 8th International Workshop on Digital Watermarking (2009)

Many methods of linguistic steganography have been proposed by using synonym-substitution to preserve the meaning of the text. However, most of these methods replace words simply according to a static synonym set without considering the context. In this paper, we present a novel method that replaces a word by its synonym on condition that its synonym is suitable for the context. A synonym's candidates are chosen according to context, therefore, in different context the candidates can be different although the word to be replaced is the same. As a result, both of the synonym set and the encoding are dynamic. In our experiment, we use Chinese language to implement our method. The experimental results show that the method is almost twice as good as other two existing methods.
Process Mapping for MPI Collective Communications
Authors: Jin Zhang, Jidong Zhai, Wenguang Chen, Weimin Zheng
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

It is an important problem to map virtual parallel processes to physical processors (or cores) in an optimized way to get scalable performance due to non-uniform communication cost in modern parallel computers. Existing work uses profile-guided approaches to optimize mapping schemes to minimize the cost of point-to-point communications automatically. However, these approaches cannot deal with collective communications and may get sub-optimal mappings for applications with collective communications.In this paper, we propose an approach called OPP (Optimized Process Placement) to handle collective communications which transforms collective communications into a series of point-to-point communication operations according to the implementation of collective communications in communication libraries. Then we can use existing approaches to find optimized mapping schemes which are optimized for both point-to-point and collective communications.We evaluated the performance of our approach with micro-benchmarks which include all MPI collective communications, NAS Parallel Benchmark suite and three other applications. Experimental results show that the optimized process placement generated by our approach can achieve significant speedup.
An Open-Control Concept for a Holonic Multiagent System
Authors: Emmanuel Adam, Thierry Berger, Yves Sallez, Damien Trentesaux
Venue: Proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2009)

MAS are particularly adapted to deal with distributed and dynamic environment. The management of business workflow, or data flow, flexible manufacturing systems is typically a good application field for them. This kind of application requires centralization of the data control and flexibility to face with changes on the network. In the context of FMS, where products and resources entities can be seen as active, this paper presents the open-control concept and gives an example of its instantiation with holonic scheme. The open-control concept proposed in this paper exhibits the classic explicit control, as well as an innovative type of control called implicit control that allows system entities to be influenced via an Optimization Mechanism (OM). We illustrate our proposition by an implementation on a flexible assembly cell in our university.
Monte Carlo Localization of Mobile Sensor Networks Using the Position Information of Neighbor Nodes
Authors: Hamid Mirebrahim, Mehdi Dehghan
Venue: Proceedings of the 8th International Conference on Ad-Hoc, Mobile and Wireless Networks (2009)

Localization is a fundamental problem in wireless sensor networks. Most existing localization algorithm is designed for static sensor networks. There are a few localization methods for mobile sensor networks. However, Sequential Monte Carlo method (SMC) has been used in localization of mobile sensor networks recently. In this paper, we propose a localization algorithm based on SMC which can improve the location accuracy. A new method is used for sample generation. In that, samples distributes uniformly over the area from which samples are drawn instead of random generation of samples in that area. This can reduces the number of required samples; besides, this new sample generation method enables the algorithm to estimate the maximum location error of each node more accurately. Our algorithm also uses the location estimation of non-anchor neighbor nodes more efficiently than other algorithms. This can improve the localization estimation accuracy highly.
On progressively censored competing risks data for Weibull distributions
Authors: Bhuvanesh Pareek, Debasis Kundu, Sumit Kumar
Venue: Computational Statistics Data Analysis (2009)

In survival analysis, or in reliability study, an investigator is often interested in the assessment of a specific risk in the presence of other risk factors. It is well known as the competing risks problem in statistical literature. Moreover, censoring is inevitable in any life testing or reliability study. In this paper, we consider a very general censoring scheme, namely a progressive censoring scheme. It is further assumed that the lifetime distribution of the individual causes are independent and Weibull-distributed with the same shape parameters but different scale parameters. We obtain the maximum likelihood and approximate maximum likelihood estimates of the unknown parameters. We also compute the observed Fisher information matrix using the missing information principles, and use them to compute the asymptotic confidence intervals. Monte Carlo simulations are performed to compare the performances of the different methods, and one data set is analyzed for illustrative purposes. We also discuss different optimality criteria, and selected optimal progressive censoring plans are presented.
Stochastic Process Creation
Authors: Javier Esparza
Venue: Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009 (2009)

In many areas of computer science entities can "reproduce", "replicate", or "create new instances". Paramount examples are threads in multithreaded programs, processes in operating systems, and computer viruses, but many others exist: procedure calls create new incarnations of the callees, web crawlers discover new pages to be explored (and so "create" new tasks), divide-and-conquer procedures split a problem into subproblems, and leaves of tree-based data structures become internal nodes with children. For lack of a better name, I use the generic term systems with process creation to refer to all these entities.
Two-dimensional discriminant locality preserving projections for face recognition
Authors: Yu Weiwei
Venue: Pattern Recognition Letters (2009)

One of the key issues of face recognition is to extract the features of face images. 2D-DLPP is a new feature extraction method for face recognition. 2D-DLPP benefits from three techniques, i.e., locality preserving projections (LPP), image based projection and discriminant analysis. Firstly, LPP can optimally preserve the local structure of the samples. Secondly, compared to vector based projection, image based projection can avoid the small sample size problem and give more spatial structural information of image. Finally, discriminant analysis applied in 2D-DLPP can improve recognition performance by maximizing the interpersonal distance and minimizing the intrapersonal distance. The experimental results show that 2D-DLPP is robust and has better face recognition performance than other methods. In addition, row projection and column projection of 2D-DLPP are discussed and compared. Though the expressions of the two projections are similar, the experimental results of them are different. Therefore, it is necessary to select a suitable projection method for a certain face image database.
Diagnosis as approximate belief state enumeration for probabilistic concurrent constraint automata
Authors: Oliver B. Martin, Brian C. Williams, Michel D. Ingham
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

As autonomous spacecraft and other robotic systems grow increasingly complex, there is a pressing need for capabilities that more accurately monitor and diagnose system state while maintaining reactivity. Mode estimation addresses this problem by reasoning over declarative models of the physical plant, represented as a factored variant of Hidden Markov Models (HMMs), called Probabilistic Concurrent Constraint Automata (PCCA). Previous mode estimation approaches track a set of most likely PCCA state trajectories, enumerating them in order of trajectory probability. Although Best-First Trajectory Enumeration (BFTE) is efficient, ignoring the additional trajectories that lead to the same state can significantly underestimate the true state probability and result in misdiagnosis. This paper introduces an innovative belief approximation technique, called Best-First Belief State Enumeration (BFBSE), that addresses this limitation by computing estimate probabilities directly from the HMM belief state update equations. Theoretical and empirical results show that BFBSE significantly increases estimator accuracy, uses less memory, and requires less computation time when enumerating a moderate number of estimates for the approximate belief state of subsystem sized models.
Interference Temperature Estimation Based on the Detection and Estimation of Angles of Arrival of Multiple Wide-Band Sources in Cognitive Radio Sensor Networks
Authors: Wei Ma, Mu Qing Wu, Guan Nan Li, Ning Zhang
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Majority of evaluation methods on interference temperature algorithms are based on the assumption that either the interference signals or the user’s signals are no directions. This is a mathematical constraint that is not satisfied in many applications. In fact, without consideration the signal directions increase estimation interference temperature, that is, reduce the frequency utilizing chance for users. In this paper, we consider situations where the interference signals and user’s signals have directions in cognitive radio sensor networks. We propose an algorithm that estimates the interference temperature of this model using a generalization of the DOA（direction of arrival algorithm. From this, we find the interference temperature and show that it does become smaller. We compare our method to the conventional (without considering directions) algorithm. The simulation studies show that the new method outperforms the conventional algorithm by reducing the estimation interference temperature and improving the frequency spectrum efficiency.
Finite Curvature Continuous Polar Patchworks
Authors: K. Karčiauskas, J. Peters
Venue: Proceedings of the 13th IMA International Conference on Mathematics of Surfaces XIII (2009)

We present an algorithm for completing a C 2 surface of up to degree bi-6 by capping an n-sided hole with polar layout. The cap consists of n tensor-product patches, each of degree 6 in the periodic and degree 5 in the radial direction. To match the polar layout, one edge of these patches is collapsed.We explore and compare with alternative constructions, based on more pieces or using total-degree, triangular patches.
SBAS/INS Hybridization Simulation and Performance Analysis
Authors: Shuguang Sun
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

An inertial navigation system/satellite based augmentation system (INS/SBAS) hybridization model has been built to analyze the performance of the system, using Kalman filter to estimate the system errors and calibrate the INS errors. Comparison was made between the original INS position data obtained from a flight test and the hybridized position data. Figures obtained from hybridization simulation have been plotted, with the explanation and conclusion got from the simulation.
Holonic Manufacturing Paint Shop
Authors: Morten Lind, Olivier Roulet-Dubonnet, Per Åge Nyen, Lars Tore Gellein, Terje Lien, Amund Skavhaug
Venue: Proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2009)

In pursuit of flexibility and agility within discrete manufacturing, the surrounding logistics and handling processes of a paint shop is under construction as a laboratory prototype application. Holonic Manufacturing seems to be a promising strategic paradigm and architecture to use for a system characterised by production logistics and control. This paper describes the physical devices to be used; the desired functionality; and the basic logic control designed. Additionally, the ideas for holonification based on the already designed logic control is presented.
Exploiting Stream Request Locality to Improve Query Throughput of a Data Integration System
Authors: Rubao Lee, Zhiwei Xu
Venue: IEEE Transactions on Computers (2009)

This paper focuses on the problem of improving throughput of distributed query processing in an RDBMS-based data integration system. Although a buffer pool can be used in an RDBMS to cache disk pages in memory to reduce disk accesses, it cannot be used for data integration queries since its foundation, the memory-disk hierarchy, does not exist. The lack of a data sharing mechanism limits system throughput because unnecessary data requests increase burden on data sources and redundant resultant data transfers waste network bandwidth. To address the problem, we present a new technique called request window, which can detect and exploit data sharing opportunities among concurrent queries. Request window exploits a new stream request locality which reflects common query interests among independent users in a short time period. The existence of such a locality makes it possible to collect a group of related data requests and process them as a batch by request window. Evaluation on a PostgreSQL-based data integration system shows that request window can significantly increase system throughput when running a distributed TPC-H workload.
Near-optimal search in continuous domains
Authors: Samuel Ieong, Nicolas Lambert, Yoav Shoham, Ronen Brafman
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

We investigate search problems in continuous state and action spaces with no uncertainty. Actions have costs and can only be taken at discrete time steps (unlike the case with continuous control). Given an admissible heuristic function and a starting state, the objective is to find a minimum-cost plan that reaches a goal state. As the continuous domain does not allow the tight optimality results that are possible in the discrete case (for example by A*), we instead propose and analyze an approximate forward-search algorithm that has the following provable properties. Given a desired accuracy Ε, and a bound d on the length of the plan, the algorithm computes a lower bound L on the cost of any plan. It either (a) returns a plan of cost L that is at most Ε more than the optimal plan, or (b) if, according to the heuristic estimate, there may exist a plan of cost L of length > d, returns a partial plan that traces the first d steps of such plan. To our knowledge, this is the first algorithm that provides optimality guarantees in continuous domains with discrete control and without uncertainty.
Pilot Confidence with ATC Automation Using Cockpit Situation Display Tools in a Distributed Traffic Management Environment
Authors: Sarah V. Ligda, Nancy Johnson, Joel Lachter, Walter W. Johnson
Venue: Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009 (2009)

NASA's Flight Deck Display Research Laboratory recently investigated air traffic automation designed to alleviate groundside workload in high traffic environments. This paper examines the data from post-experiment debriefings. We found that pilots are comfortable reviewing automated conflict resolutions, as well as modifying those resolutions before execution. The pilots were less comfortable with an automated system that had no pilot or controller human-in-the-loop review process. This traffic management concept will not be optimally achieved if pilots do not trust automation without a human review process in every conflict situation. While initial development of these systems should focus on ways to effectively enable such reviews of the automation, confidence can be expected to increase as pilots develop first-hand experience with the system.
Predicting Links in Social Networks Using Text Mining and SNA
Authors: Alon Bartal, Elan Sasson, Gilad Ravid
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Lately there is great progress in business organizations perception towards social aspects. Competitive organizations need to create innovation and segregate in the market. Business interactions help reaching those goals but finding the effective interactions is a challenge. We propose a prediction method, based on Social Networks Analysis (SNA) and text data mining (TDM), for predicting which nodes in a social network will be linked next. The network which is used to demonstrate the proposed prediction method is composed of academic co-authors who collaborated on writing articles. Without loss of generality, the academic co-authoring network demonstrates the proposed prediction procedure due to its similarity to other networks, such as business co-operation networks. The results show that the best prediction is achieved by incorporating TDM with SNA.
POS tagging of dialectal Arabic: a minimally supervised approach
Authors: Kevin Duh, Katrin Kirchhoff
Venue: Proceedings of the ACL Workshop on Computational Approaches to Semitic Languages (2005)

Natural language processing technology for the dialects of Arabic is still in its infancy, due to the problem of obtaining large amounts of text data for spoken Arabic. In this paper we describe the development of a part-of-speech (POS) tagger for Egyptian Colloquial Arabic. We adopt a minimally supervised approach that only requires raw text data from several varieties of Arabic and a morphological analyzer for Modern Standard Arabic. No dialect-specific tools are used. We present several statistical modeling and cross-dialectal data sharing techniques to enhance the performance of the baseline tagger and compare the results to those obtained by a supervised tagger trained on hand-annotated data and, by a state-of-the-art Modern Standard Arabic tagger applied to Egyptian Arabic.
A Physical Model of Time-of-Flight 3D Imaging Systems, Including Suppression of Ambient Light
Authors: Mirko Schmidt, Bernd Jähne
Venue: Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging (2009)

We have developed a physical model of continuous-wave Time-of-Flight cameras, which focuses on a realistic reproduction of the sensor data. The derived simulation gives the ability to simulate data acquired by a ToF system with low computational effort. The model is able to use an arbitrary optical excitation and to simulate the sampling of a target response by a two-tap sensor, which can use any switching function. Nonlinear photo response and pixel saturation, as well as spatial variations from pixel to pixel like photo response non-uniformity (PRNU) and dark signal non-uniformity (DSNU) can be modeled. Also the influence of interfering background light and on-sensor suppression of ambient light can be simulated.The model was verified by analyzing two scenarios: The cameras response to an increasing, homogeneous irradiation as well as the systematic phase deviation caused by higher harmonics of the optical excitation. In both scenarios the model gave a precise reproduction of the observed data.
Mobile and Ubiquitous Commerce: Advanced E-business Methods
Authors: Milena Head, Milena Head, Eldon Y. Li
Venue:  (2009)

Mobility and ubiquity are among the most important technological and market trends of the 21st century due to the wide deployment of wireless data communication networks and the explosive growth of mobile users. Mobile and Ubiquitous Commerce: Advanced E-Business Methods advances the understanding of management methods, information technology, and their joint application in business processes. This Premier Reference Source covers theories and practices of business technologies, enterprise management, Internet adoption, and information technologies related to electronic business.