ppxscal/embedding_network huggingface dataset:
Technical Section: CHuMI viewer: Compressive huge mesh interactive viewer
Authors: Clément Jamin, Pierre-Marie Gandoin, Samir Akkouche
Venue: Computers and Graphics (2009)

The preprocessing of large meshes to provide and optimize interactive visualization implies a complete reorganization that often introduces significant data growth. This is detrimental to storage and network transmission, but in the near future could also affect the efficiency of the visualization process itself, because of the increasing gap between computing times and external access times. In this article, we attempt to reconcile lossless compression and visualization by proposing a data structure that radically reduces the size of the object while supporting a fast interactive navigation based on a viewing distance criterion. In addition to this double capability, this method works out-of-core and can handle meshes containing several hundred million vertices. Furthermore, it presents the advantage of dealing with any n-dimensional simplicial complex, including triangle soups or volumetric meshes, and provides a significant rate-distortion improvement. The performance attained is near state-of-the-art in terms of the compression ratio as well as the visualization frame rates, offering a unique combination that can be useful in numerous applications.
Asymptotic normality and confidence intervals for inverse regression models with convolution-type operators
Authors: Nicolai Bissantz, Melanie Birke
Venue: Journal of Multivariate Analysis (2009)

We consider inverse regression models with convolution-type operators which mediate convolution on R^d (d>=1) and prove a pointwise central limit theorem for spectral regularisation estimators which can be applied to construct pointwise confidence regions. Here, we cope with the unknown bias of such estimators by undersmoothing. Moreover, we prove consistency of the residual bootstrap in this setting and demonstrate the feasibility of the bootstrap confidence bands at moderate sample sizes in a simulation study.
Manifold denoising as preprocessing for finding natural representations of data
Authors: Matthias Hein, Markus Maier
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

A natural representation of data is given by the parameters which generated the data. If the space of parameters is continuous, then we can regard it as a manifold. In practice, we usually do not know this manifold but we just have some representation of the data, often in a very high-dimensional feature space. Since the number of internal parameters does not change with the representation, the data will effectively lie on a low-dimensional submanifold in feature space. However, the data is usually corrupted by noise, which particularly in high-dimensional feature spaces makes it almost impossible to find the manifold structure. This paper reviews a method called Manifold Denoising, which projects the data onto the submanifold using a diffusion process on a graph generated by the data. We will demonstrate that the method is capable of dealing with non-trival high-dimensional noise. Moreover, we will show that using the denoising method as a preprocessing step, one can significantly improve the results of a semi-supervised learning algorithm.
Efficient constrained local model fitting for non-rigid face alignment
Authors: Simon Lucey, Yang Wang, Mark Cox, Sridha Sridharan, Jeffery F. Cohn
Venue: Image and Vision Computing (2009)

Active appearance models (AAMs) have demonstrated great utility when being employed for non-rigid face alignment/tracking. The ''simultaneous'' algorithm for fitting an AAM achieves good non-rigid face registration performance, but has poor real time performance (2-3fps). The ''project-out'' algorithm for fitting an AAM achieves faster than real time performance (>200fps) but suffers from poor generic alignment performance. In this paper we introduce an extension to a discriminative method for non-rigid face registration/tracking referred to as a constrained local model (CLM). Our proposed method is able to achieve superior performance to the ''simultaneous'' AAM algorithm along with real time fitting speeds (35fps). We improve upon the canonical CLM formulation, to gain this performance, in a number of ways by employing: (i) linear SVMs as patch-experts, (ii) a simplified optimization criteria, and (iii) a composite rather than additive warp update step. Most notably, our simplified optimization criteria for fitting the CLM divides the problem of finding a single complex registration/warp displacement into that of finding N simple warp displacements. From these N simple warp displacements, a single complex warp displacement is estimated using a weighted least-squares constraint. Another major advantage of this simplified optimization lends from its ability to be parallelized, a step which we also theoretically explore in this paper. We refer to our approach for fitting the CLM as the ''exhaustive local search'' (ELS) algorithm. Experiments were conducted on the CMU MultiPIE database.
Programming Wireless Sensor Networks in a Self-Stabilizing Style
Authors: Christoph Weyer, Volker Turau, Andreas Lagemann, Jörg Nolte
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

Wireless sensor networks operate in an unstable environment and thus are subject to arbitrary transient faults. Self-stabilization is a promising technique to add tolerance against transient faults in a self-contained non-masking way. A core factor for the applicability of a given self-stabilizing algorithm is its convergence time. This paper analyses the average stabilization time of three algorithms commonly regarded as central building blocks for wireless sensor networks. The analysis is accomplished with SelfWISE, a framework providing programming abstractions for self-stabilizing algorithms. The performed analysis considers the target models as well as network size and density. This demonstrates the usability of SelfWISE for evaluating self-stabilizing algorithms under a wide range of models.
Low Power Strategy Design for Battery Management System
Authors: Yuheng Li, Xuezhe Wei, Zechang Sun
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Battery Management System (BMS) is widely used in vehicle battery pack to ensure high performance of battery. However, at present, general designs for BMS only focus on battery management in driving condition, which may cause electric energy waste when the vehicle stays long in standby condition. This article designs a low power strategy BMS for vehicle battery, which is able to switch from one mode to another according to vehicle’s condition, in order to realize low power strategy without decreasing the managing effect of BMS. Experimental result shows that this design can effectively reduce power consumption of BMS.
Designing a Game Controller for Novice HALO3 Players
Authors: Matthijs Kwak, Ben Salem
Venue: Proceedings of the 8th International Conference on Entertainment Computing (2009)

This paper describes the process of designing and developing an intuitive controller that helps lower the threshold for novice gamers to play Halo 3. To help novices to master the controller, most controls have been replaced with rich and meaningful interaction. To help novices understand the game, extra feedback channels have been added to reinforce information given onscreen so critical information is not missed.
Modeling Multi-agent Domains in an Action Languages: An Empirical Study Using $\mathcal{C}$
Authors: Chitta Baral, Tran Cao Son, Enrico Pontelli
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

In the last two decades there has been a lot of research on action languages and reasoning about actions. Most of this research assume a domain with a single agent and possibly the environment. In this short paper we explore the relevance of this research vis-a-vis modeling multi-agent domains. We use the action language $\mathcal{C}$ and show that with minimal extensions it can capture several multi-agent domains from the literature.
The TUNA-REG Challenge 2009: overview and evaluation results
Authors: Albert Gatt, Anja Belz, Eric Kow
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

The TUNA-REG'09 Challenge was one of the shared-task evaluation competitions at Generation Challenges 2009. TUNA-REG'09 used data from the TUNA Corpus of paired representations of entities and human-authored referring expressions. The shared task was to create systems that generate referring expressions for entities given representations of sets of entities and their properties. Four teams submitted six systems to TUNA-REG'09. We evaluated the six systems and two sets of human-authored referring expressions using several automatic intrinsic measures, a human-assessed intrinsic evaluation and a human task performance experiment. This report describes the TUNA-REG task and the evaluation methods used, and presents the evaluation results.
Sine-fitting multiharmonic algorithms implemented by artificial neural networks
Authors: J. R. Salinas, F. Garcia-Lagos, G. Joya, F. Sandoval
Venue: Neurocomputing (2009)

A new method designed to perform high-accuracy spectral analysis, based on ADALINE artificial neural networks (ANNs), is proposed. The proposed network is able to accurately calculate the fundamental frequency and the harmonic content of an input signal. The method is especially useful in high-precision digital measurement systems in which periodical signals are involved, i.e. digital watt meters. Most of these systems use spectral analysis algorithms as an intermediate step for the computation of the magnitudes of interest. The traditional spectral analysis methods require synchronous sampling, which introduce limitations to the sampling circuitry. Sine-fitting multiharmonics algorithms resolve the hardware limitations concerning the synchronous sampling but have some limitations with regard to the phase of the array of samples. The new implementation of sine-fitting multiharmonics algorithms based on ANN eliminates these limitations.
UPC: experiments with joint learning within SemEval task 9
Authors: Lluís Màrquez, Lluís Padró, Mihai Surdeanu, Luis Villarejo
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

This paper describes UPC's participation in the SemEval-2007 task 9 (M&agrave;rquez et al., 2007). We addressed all four subtasks using supervised learning. The paper introduces several novel issues: (a) for the SRL task, we propose a novel reranking algorithm based on the re-ranking Perceptron of Collins and Duffy (2002); and (b) for the same task we introduce a new set of global features that extract information not only at proposition level but also from the complete set of frame candidates. We show that in the SemEval setting, i.e., small training corpora, this approach outperforms previous work. Additionally, we added NSD and NER information in the global SRL model but this experiment was unsuccessful.
A New Algorithm for Random Harmonic Current Detection Based on Mathematical Morphology
Authors: Wang Jing, Liu Di-chen, Liu Pan, Zhao jie
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

Active Power Filter is an important device in eliminating harmonic pollution and the key problem in APF is how to detect the harmonic current accurately. In this paper a mathematical morphology algorithm for random harmonic current detection is presented. This algorithm which is based on Instantaneous Reactive Power Theory can detect positive and negative sequence component of random harmonic current fast and accurately. To different harmoniccurrents, the lengths of the structural elements can be automatically adjusted to the optimal value in this algorithm. In addition, the algorithm conquers the error which is caused by fixed structure element and has a high precision and high stability. Analysis and simulation prove the correctness of the algorithm.
A Perceptual Data Repository for Polygonal Meshes
Authors: Samuel Silva, Beatriz Sousa Santos, Carlos Ferreira, Joaquim Madeira
Venue: Proceedings of the 2009 Second International Conference in Visualisation (2009)

A repository containing perceived quality data for polygonal meshes, obtained through observer studies, is presented. It includes information regarding the experimental methodology, protocol and models used,with the purpose of allowing researchers to use it, e.g., for a faster preliminary assessment of their perceived quality metrics without the overhead of designing and performing an observer study.
User-Experience Development
Authors: Aaron Marcus
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

Developers worldwide wish to understand user-experience development (UXD). UXD comprises activities in user-centered design of user experience, specifically user-interface development (metaphors, mental models, navigation, interaction, and appearance) that are useful for planning, research, analysis, design, implementation, evaluation, and documentation of products/services across a wide number of platforms. This paper summarizes some key concepts and terms.
Detecting Structural Changes and Command Hierarchies in Dynamic Social Networks
Authors: Romain Bourqui, Frédéric Gilbert, Paolo Simonetto, Faraz Zaidi, Umang Sharan, Fabien Jourdan
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Community detection in social networks varying with time is a common yet challenging problem whereby efficient visualization of evolving relationships and implicit hierarchical structure are important task. The main contribution of this paper is towards establishing a framework to analyze such social networks. The proposed framework is based on dynamic graph discretization and graph clustering.The framework allows detection of major structural changes over time, identifies events analyzing temporal dimension and reveals command hierarchies in social networks.We use the Catalano/Vidro dataset for empirical evaluation and observe that our framework provides a satisfactory assessment of the social and hierarchical structure present in the dataset.
Degradation of Rhodamine B Using UV/Cu2+/H202 System
Authors: Hong Jun, Wu Chengcheng, Lu Sijia, Cui Yanping
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

It is difficult to treat industry wastewater which contains both heavy metals and refractory organic compounds. However, the Fenton-like reaction system using heavy metal ions in wastewater to decompose organics seems a promising method, which would have a positive effect on pollution reduction and wastes re-utilization. This paper is set out to comparatively study the effectiveness of UV/H2O2/metal ion systems on a representative substrate as Rhodamine B. Results show that the UV/Cu2+/H2O2 system exhibited high degradation efficiency on Rhodamine B which was completely degraded in 30 min. Also the degradation obeyed first-order kinetic equation. Furthermore, influences of Cu2+ concentration, methods of H2O2 addition, pH and UV radiation on RhB degradation were studied, respectively, for the UV/Cu2+/H2O2 system. Optimal reaction conditions were found to be [Cu2+]=0.324 mmol/L, [H2O2]=0.118 mmol/L and ways of adding H2O2 by two or more times rather than one, pH=3, necessity of UV radiation. Moreover, the coexistence of Mn2+ with UV/Cu2+/H2O2 enhanced the degradation efficiency.
Simulated Iterative Classification A New Learning Procedure for Graph Labeling
Authors: Francis Maes, Stéphane Peters, Ludovic Denoyer, Patrick Gallinari
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

Collective classification refers to the classification of interlinked and relational objects described as nodes in a graph. The Iterative Classification Algorithm (ICA) is a simple, efficient and widely used method to solve this problem. It is representative of a family of methods for which inference proceeds as an iterative process: at each step, nodes of the graph are classified according to the current predicted labels of their neighbors. We show that learning in this class of models suffers from a training bias. We propose a new family of methods, called Simulated ICA, which helps reducing this training bias by simulating inference during learning. Several variants of the method are introduced. They are both simple, efficient and scale well. Experiments performed on a series of 7 datasets show that the proposed methods outperform representative state-of-the-art algorithms while keeping a low complexity.
An Approach to Testing Web Applications Based on Probable FSM
Authors: Qian Zhongsheng
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Web testing is an effective technique to ensure the quality of Web applications. Unfortunately, it is hard to directly employ the traditional test theories and methodologies because of the particularities and complexities of Web applications. Testing Web applications raises new problems and faces very high challenges. This work proposes a practical Web usage model based on probable FSM. According to the probable FSM usage model, it details the process of generating test cases. The testing process is based on the idea that different parts of the Web application have different execution frequency. Therefore, the test cases produced ensure that the failures occurring most frequently in operational uses will be found early in the test process. 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
3DNBS: A Data De-duplication Disk-Based Network Backup System
Authors: Tianming Yang, Dan Feng, Jingning Liu, Yaping Wan, Zhongying Niu, Yuchang Ke
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

Traditionally, backup and archiving have been performed on tapes. With the rapid advances in disk storage technology witnessed in recent years, it becomes practical to use disks other than tape libraries as backend storage device for a backup system. For such a disk-based system, storage space efficiency is essential. Since traditional backup method cannot eliminate redundancies during backup, a new data deduplication backup technique should be developed to provide more efficient data storage at the system.This paper describes the design and performance evaluation of a data de-duplication disk-based network backup system,called 3DNBS. 3DNBS breaks files into variable sized chunks using content-defined chunking (CDC) for the purpose of duplication detection. Chunks are indexed and addressed by hashing their content, which leads to intrinsically single instance storage. Experimental results show that in comparison with traditional backup method such as Bacula, 3DNBSpresents dramatic reduction in required storage space on various workloads. By eliminating duplicated data, 3DNBS also reduces the size of data to be transmitted, hence reducing time to perform backup in a bandwidth constraint environment.
From Usability to Playability: Introduction to Player-Centred Video Game Development Process
Authors: Jose Luis González Sánchez, Natalia Padilla Zea, Francisco L. Gutiérrez
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

While video games have traditionally been considered simple entertainment devices, nowadays they occupy a privileged position in the leisure and entertainment market, representing the fastest-growing industry globally. We regard the video game as a special type of interactive system whose principal aim is to provide the player with fun and entertainment. In this paper we will analyse how, in Video Games context, Usability alone is not sufficient to achieve the optimum Player Experience. It needs broadening and deepening, to embrace further attributes and properties that identify and describe the Player Experience. We present our proposed means of defining Playability. We also introduce the notion of Facets of Playability. Each facet will allow us to characterize the Playability easily, and associate them with the different elements of a video game. To guarantee the optimal Player Experience, Playability needs to be assessed throughout the entire video game development process, taking a Player-Centred Video Game Design approach.
Reconfiguration of List Edge-Colorings in a Graph
Authors: Takehiro Ito, Marcin Kamiński, Erik D. Demaine
Venue: Proceedings of the 11th International Symposium on Algorithms and Data Structures (2009)

We study the problem of reconfiguring one list edge-coloring of a graph into another list edge-coloring by changing one edge color at a time, while at all times maintaining a list edge-coloring, given a list of allowed colors for each edge. First we show that this problem is PSPACE-complete, even for planar graphs of maximum degree 3 and just six colors. Then we consider the problem restricted to trees. We show that any list edge-coloring can be transformed into any other under the sufficient condition that the number of allowed colors for each edge is strictly larger than the degrees of both its endpoints. This sufficient condition is best possible in some sense. Our proof yields a polynomial-time algorithm that finds a transformation between two given list edge-colorings of a tree with n vertices using O(n 2) recolor steps. This worst-case bound is tight: we give an infinite family of instances on paths that satisfy our sufficient condition and whose reconfiguration requires ¿(n 2) recolor steps.
A Triangular Formation Strategy for Collective Behaviors of Robot Swarm
Authors: Xiang Li, M. Fikret Ercan, Yu Fai Fung
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part I (2009)

This paper presents, a novel decentralized control strategy, named Triangular Formation Algorithm (TFA), for a swarm of simple robots. The TFA is a local interaction strategy which basically makes three neighboring robots to form a regular triangular lattice. This strategy requires minimal conditions for robots and it can be easily realized with real robots. The TFA is executed by every member of the swarm asynchronously. For swarm obstacle avoidance, a simplified artificial physical model is introduced to work with the TFA. Simulation results showed that the global behaviors of swarm such as aggregation, flocking and obstacle avoidance in an unknown environment can be achieved using the TFA and obstacle avoidance mechanism.