ppxscal/embedding_network huggingface dataset:
Surface reconstruction from point cloud of human body by clustering
Authors: Takuya Funatomi, Isao Moro, Shinobu Mizuta, Michihiko Minoh
Venue: Systems and Computers in Japan (2006)

This paper proposes a method in which the body surface is reconstructed from a point cloud (set of points) on the human body acquired by a device such as a laser range finder. The method constructs the surface appropriately for the human body by clustering the point cloud at body sections such as the chest and the upper arm. The clustering is performed as follows. A simple human model composed of cylinders, ellipsoidal columns, and hemispheres is assumed. The posture is estimated by matching the human body model to the point cloud data. Based on the estimated posture, the point cloud is assigned to body sections. Since the posture is inferred from the point cloud, the method is effective not only for an upright standing posture, but for point cloud data obtained from an arbitrary posture. Experiments were performed to apply the method to simulation data and measured data, and it was shown that a realistic surface could be reconstructed. The surface can be reconstructed for postures other than the upright standing posture. The effectiveness of the proposed method is thus verified. &copy; 2006 Wiley Periodicals, Inc. Syst Comp Jpn, 37(11): 44&ndash;56, 2006; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.20230
On error-tolerant DNA screening
Authors: Weili Wu, Yaochun Huang, Xiao Huang, Yingshu Li
Venue: Discrete Applied Mathematics (2006)

Given n clones with some positive ones, the problem of DNA screening is to identify all positive clones with a set of tests each on a subset of clones, called a pool and the outcome is either the pool contains a positive clone or not. In this paper, we show that for a class of designs, if we apply those for samples with d positive clones to samples with at most d - 1 positive clones, the error-tolerant property will have an interesting improvement. We also make a remark on decoding method for k-error-correcting d-disjunct matrix.
Problem-Based Learning Using Mobile Devices
Authors: Christian Wattinger, Duc Phuong Nguyen, Peter Fornaro, Martin Guggisberg, Tibor Gyalog, Helmar Burkhart
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Small handheld devices such as PDAs and smart phones become more and more popular. Thus, we are seeing a growing number of projects using mobile devices for educational purposes. Due to the limitations of screen size, CPU performance, and memory size, software development for mobile devices is challenging. More critical argument is about the lack of pedagogic and didactic concepts on the usage of mobile devices in education. In this paper, we present a system using mobile devices which supports research experiences for students in a laboratory context. The system allows students to efficiently monitor and control their scientific experiments at anytime, from anywhere. We describe several usage scenarios in the area of nanoscience studies, where the remote control of microscopes is mandatory. We present our system architecture and describe the implementation based on open-source software.
DDoS defense by offense
Authors: Michael Walfish, Mythili Vutukuru, Hari Balakrishnan, David Karger, Scott Shenker
Venue: ACM SIGCOMM Computer Communication Review (2006)

This paper presents the design, implementation, analysis, and experimental evaluation of speak-up, a defense against application-level distributed denial-of-service (DDoS), in which attackers cripple a server by sending legitimate-looking requests that consume computational resources (e.g., CPU cycles, disk). With speak-up, a victimized server encourages all clients, resources permitting, to automatically send higher volumes of traffic. We suppose that attackers are already using most of their upload bandwidth so cannot react to the encouragement. Good clients, however, have spare upload bandwidth and will react to the encouragement with drastically higher volumes of traffic. The intended outcome of this traffic inflation is that the good clients crowd out the bad ones, thereby capturing a much larger fraction of the server's resources than before. We experiment under various conditions and find that speak-up causes the server to spend resources on a group of clients in rough proportion to their aggregate upload bandwidth. This result makes the defense viable and effective for a class of real attacks.
A new approach to characterizing the relative position of two ellipses depending on one parameter
Authors: Fernando Etayo, Laureano Gonzalez-Vega, Natalia del Rio
Venue: Computer Aided Geometric Design (2006)

By using several tools coming from Real Algebraic Geometry, Computer Algebra and Projective Geometry (Sturm-Habicht sequences and the classification of pencils of conics in P2(R)), a new approach for characterizing the ten relative positions of two ellipses is introduced.Each relative position is exclusively characterized by a set of equalities and inequalities depending only on the matrices defining the two considered ellipses and does not require in advance the computation or knowledge of the intersection points between them.Moreover, this characterization is specially well adapted for computionally treating the case where the considered ellipses depend on one or several parameters.
Motion Trajectory Classification for Visual Surveillance and Tracking
Authors: Shiloh L. Dockstader
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

In this paper we present a video surveillance system for automated border and checkpoint analysis. The described system employs automated feature extraction and tracking to ascertain vehicle size, speed, and response to an interrogating vibration for vehicle bounce signature analysis. To increase the overall robustness of the surveillance system, we introduce a novel approach to invalid feature filtering. In particular, we use a hidden Markov model trained to simultaneously recognize specific coarse motion trajectories and tracking failures. The proposed recognition and filtering scheme effectively identifies erroneously tracked features and removes them prior to any subsequent motion analysis tasks. The result is a significant increase in classification and recognition accuracy. We demonstrate the efficacy of the suggested technique on a variety of video surveillance sequences.
Method and Environment for the Retrieval of Structural Music Information
Authors: Alberto Pinto, Goffredo Haus
Venue: Proceedings of the Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (2006)

Existing solutions for searching for appropriate music content rely on methods like string edit distances or functional approaches (as for the symbolic level) or features extraction methods (as for the audio level) that cannot provide structural similarity information. Our results in structural similarity measures for music information retrieval rely on graph theory and provide new tools for extract characterizing structural quantities from musical data (both symbolic and audio) to be implemented within an integrated query environment. The improvements regard the use of the graph model of musical data at different levels, the MX format for the representation of musical work and the new user interfaces for the navigation of musical source material.
An integrated framework for enabling effective data collection and statistical analysis with ns-2
Authors: Claudio Cicconetti, Enzo Mingozzi, Giovanni Stea
Venue: Proceeding from the 2006 workshop on ns-2: the IP network simulator (2006)

The Network Simulator 2 (ns-2) is an open source tool for network simulation. When planning for large-scale simulation experiments, an efficient and flexible data collection and a statistically sound output data analysis are important aspects to keep in mind. Unfortunately, ns-2 offers little support for data collection, and statistical analysis of the simulation results is most often performed offline, using either home made code or available packages, which are not integrated with ns-2. In this paper we describe two complementary contributions: the first one consists of a set of C++ modules, that allow a flexible and efficient data collection; the second one is a software framework, which is fully integrated with ns-2, that performs all the operations required to carry out simulation experiments in a statistically sound way. Our framework allows a user to significantly reduce the postprocessing overhead and to save simulation time, especially with large-scale simulations. Our code is publicly available at [3].
Age-related Changes in Brain Activity across the Adult Lifespan
Authors: Cheryl L. Grady, Mellanie V. Springer, Donaya Hongwanishkul, Anthony R. Mcintosh, Gordon Winocur
Venue: Journal of Cognitive Neuroscience (2006)

A number of theories have emerged to explain the well-studied changes in memory that occur with age. Many of these theories invoke mechanisms that have the potential to affect multiple cognitive domains, in addition to memory. Such mechanisms include alterations in attentional or inhibitory function, or dysfunction of specific brain areas, such as the frontal lobes. To gain insight into these mechanisms, we used functional magnetic resonance imaging to examine brain activity during encoding and recognition tasks in young, middle-aged, and older adults to identify correlations between age and brain activity across the various tasks. The goal was to see whether these correlations were task-specific or common across tasks, and to determine whether age differences emerged in a linear fashion over the adult years. Across all memory tasks, at both encoding and recognition, linear increases of activity with age were found in areas normally decreased during task performance (e.g., medial frontal and parietal regions), whereas activity in regions with task-related activation (e.g., dorsolateral prefrontal cortex) decreased with age. These results suggest that there is a gradual, age-related reduction in the ability to suspend non-task-related or "default-mode" activity and engage areas for carrying out memory tasks. Such an alteration in the balance between default-mode and task-related activity could account for increased vulnerability to distraction from irrelevant information, and thereby affect multiple cognitive domains.
Toward Robust Distance Metric Analysis for Similarity Estimation
Authors: Jie Yu, Qi Tian, Jaume Amores, Nicu Sebe
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

In this paper, we present a general guideline to establish the relation between a distribution model and its corresponding similarity estimation. A rich set of distance metrics, such as harmonic distance and geometric distance, is derived according to Maximum Likelihood theory. These metrics can provide a more accurate feature model than the conventional Euclidean distance (SSD) and Manhattan distance (SAD). Because the feature elements are from heterogeneous sources and may have different influence on similarity estimation, the assumption of single isotropic distribution model is often inappropriate. We propose a novel boosted distance metric that not only finds the best distance metric that fits the distribution of the underlying elements but also selects the most important feature elements with respect to similarity. We experiment with different distance metrics for similarity estimation and compute the accuracy of different methods in two applications: stereo matching and motion tracking in video sequences. The boosted distance metric is tested on fifteen benchmark data sets from the UCI repository and two image retrieval applications. In all the experiments, robust results are obtained based on the proposed methods.
Analysis of Error Sources Towards Improved Form Processing
Authors: Ujjwal Bhattacharya, Bikash Shaw, Swapan K. Parui
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

Automatic form processing is an important application of document analysis subject. Such a system requires to be trained and tested on a standard database of forms collected from real-life. However, to the best of our knowledge, the only such available databases are NIST Special Databases [1, 2]. These databases consist of images of synthesized form documents. On the other hand, recently we developed a form database [3], samples of which had been taken from the real-life. ISIFormReader, a form processing system, also developed recently [4], has been tested using these real-life samples. An intensive study of the processing errors showed that writers' idiosyncracies are one of the major reasons of such errors as analyzed in [4]. In the present paper, we investigated various other sources of errors which together cause a major concern. These include sample forms which are low in contrast, noisy, smudgy, skewed, scaled disturbing its aspect ratio and so on. An analysis of errors due to similar such sources is important towards development of an improved form processing system.
Unconditional Stability of Corrected Explicit-Implicit Domain Decomposition Algorithms for Parallel Approximation of Heat Equations
Authors: Han-Sheng Shi, Hong-Lin Liao
Venue: SIAM Journal on Numerical Analysis (2006)

A class of corrected explicit-implicit domain decomposition (CEIDD) methods is investigated for the parallel approximation of linear heat equations. Explicit-implicit domain decomposition (EIDD) methods are computationally and communicationally efficient for each time step but always suffer from small time step size restrictions. By adding an interface correction step to Kuznetsov&apos;s EIDD, the one-dimensional CEIDD procedure achieves unconditional stability without discarding the time-stepwise efficiency of the EIDD method. In order to maintain the virtues of the CEIDD method and improve the flexibility in domain partitioning, for solving multidimensional problems, special zigzag-shaped interfaces are suggested in the CEIDD method. Based on noncrossover and crossover types of zigzag interfaces, the resulting CEIDD-ZI algorithms are studied for two strategies of subdomain partition. By the energy method, it shows that the proposed algorithms, including their degenerate cases---the corrected explicit hopscotch schemes---are convergent in the discrete H1 semi-norm and L2 norm. Numerical experiments confirm the results in our analysis.
Middleware - An Effort towards Making Mobile Applications Platform Independent
Authors: Neeraj Gupta, Vishal Srivastav, M. P. S. Bhatia
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

We propose a middleware architecture for GSM mobile phones that makes applications for mobile phones platform independent to a large extent as well as the applications made using the middleware run on a wide range of devices. Currently we have considered Symbian OS and Windows CE OS. The middleware is implemented in C++ and it provides good performance in terms of memory use and execution speed. The middleware requires less than 50 KB of memory and is suitable for resource-constrained mobile phones. The first experiments verify that the middleware operates well and offers a good basis for future development.
Contrast enhancement and background suppression of chemosensor array patterns with the KIII model: Research Articles
Authors: Agustin Gutierrez-Galvez, Ricardo Gutierrez-Osuna
Venue: International Journal of Intelligent Systems (2006)

Inspired by the ability of the olfactory bulb to enhance the contrast between odor representations, we propose a new hebbian learning rule that is able to increase the separability of odor patterns from gas sensor arrays. The proposed learning rule employs a hebbian term to build associations within odors and an anti-hebbian term to reduce correlated activity across odors. In addition to increasing the separability of patterns, the new learning rule can also achieve odor background suppression when combined with a habituation term. These two functions are demonstrated on Freeman's KIII, a neurodynamics model of the olfactory system. The system is first characterized on synthetic data, and also validated on experimental data from an array of chemical sensors exposed to organic solvents. &copy; 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 937&ndash;953, 2006.
Constructing a physical layer of virtual cities for disaster mitigation
Authors: Ping Zhu, Yozo Fujino, Muneo Hori, Junji Kiyono
Venue: Proceedings of the 2005 international conference on Augmented tele-existence (2005)

This paper proposes a method of simulating natural disasters of a big city by constructing huge number of structural models of buildings using their geometries obtained from 3D GIS data.
Vigilance performance modeled as a complex adaptive system with listener event graph objects (LEGOS)
Authors: Joerg C. G. Wellbrink, Arnold H. Buss
Venue: Proceedings of the 36th conference on Winter simulation (2004)

There has been an increasing need to incorporate human performance in simulation models. Situations in which human performance is subject to degradation over time, such as vigilance tasks, are not represented. This article describes a computational model for vigilance performance embedded in a new cognitive framework that utilizes recent advances in system neuroscience, evolutionary psychology and complexity theory. The Reduced Human Performance Model (RHPM) captures human errors in monitoring tasks to a greater degree than previous attempts. RHPM is implemented as a discrete event simulation using Listener Event Graph Objects (LEGOs). The model captures leading vigilance theories and can be used as a tool to improve existing vigilance theories and to improve current monitoring procedures minimizing errors that could lead to catastrophic outcomes.
Evaluation of a universal interaction and control device for use within multiple heterogeneous display ubiquitous environments
Authors: Hannah Slay, Bruce H. Thomas
Venue: Proceedings of the 7th Australasian User interface conference - Volume 50 (2006)

This paper provides an insight into the usability of our Universal Interaction Controller (UIC), a user interface device designed to support interactions in ubiquitous computing environments equipped with multiple heterogeneous displays. The results are presented of a user study we undertook to test the intuitiveness of Ukey, our UIC input device, comparing it to a wireless gyroscopic mouse, as benchmarked against a traditional mouse. We found that with no training, users were able to perform better with the UIC than with the gyroscopic mouse, but their performance with the traditional mouse exceeded both. With an hour of additional training, participant's performance with the UIC was better than their performance with a traditional mouse when interacting between display devices.
Image-Segmentation Evaluation From the Perspective of Salient Object Extraction
Authors: Feng Ge, Song Wang, Tiecheng Liu
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Image segmentation and its performance evaluation are very difficult but important problems in computer vision. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity: For general-purpose segmentation, the ground truth and segmentation accuracy may not be well defined, while embedding the evaluation in a specific application, the evaluation results may not be extended to other applications. We present in this paper a new benchmark for evaluating image segmentation. Specifically, we formulate image segmentation as identifying the single most perceptually salient structure from an image. We collect a large variety of test images that conforms to this specific formulation, construct unambiguous ground truth for each image, and define a reliable way to measure the segmentation accuracy. We then present two special strategies to further address two important issues: (a) the most salient structures in some real images may not be unique or unambiguously defined, and (b) many available image-segmentation methods are not developed to directly extract a single salient structure. Finally, we apply this benchmark to evaluate and compare the performance of several state-of-the-art image-segmentation methods, including the normalized-cut method, the level-set method, the efficient graph-based method, the mean-shift method, and the ratio-contour method.
Plan patterns for declarative goals in AgentSpeak
Authors: Jomi Fred Hübner, Rafael H. Bordini, Michael Wooldridge
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper, we consider the use of declarative goals in the AgentSpeak programming language, originally introduced in [6]. By a declarative goal, we mean a goal that explicitly represents a state of affairs to be achieved, in the sense that, if an agent has a goal p(t1,...,tn) then it expects to eventually believe p(t1,...,tn), and only then can the goal be considered achieved. Currently, although goals form a central component of AgentSpeak programming, they are only implicit in the plans defined by the agent programmer. For example, there is no explicit way of expressing that a goal should be maintained until a certain condition holds; such temporal goal structures are hidden within the plan structures themselves. While one possibility would be to extend the language to introduce an explicit construct for declarative goals and a goal base, we show that this is unnecessary. We introduce a number of plan patterns, corresponding to common types of explicit emporal/conditional (declarative) goal structures, and show how these can be mapped into AgentSpeak code. Thus, a programmer or designer can conceive of a goal at the declarative level, and this goal will be "translated" via these patterns into standard AgentSpeak code.
Automatic Generation of a Multimedia Encyclopedia from TV Programs by Using Closed Captions and Detecting Principal Video Objects
Authors: Kikuka Miura, Ichiro Yamada, Hideki Sumiyoshi, Nobuyuki Yagi
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

This paper proposes a method for automatically generating a multimedia encyclopedia from video clips using closed-caption text information. The goal is to automatically index each video segment of the television program by the principal video object. We focus on several features of the closed-caption text style in order to identify the principal video objects. Using Quinlan's C4.5 decision-tree learning algorithm and the predicted accuracies of production rule indicators, one object noun is extracted for each video shot. To show the effectiveness of the method, we conducted experiments on the extraction of video segments in which animals appear in twenty television programs on animals and nature. We obtained a precision rate of 74.6 percent and a recall rate of 51.4 percent on the extraction of video segments in which animals appear, and generated a multimedia encyclopedia comprising 322 video clips showing 82 kinds of animals.
Minimizing total setup cost for a metal casting company
Authors: Xue-Ming Yuan, Hsien Hui Khoo, Trevor A. Spedding, Ian Bainbridge, David M. R. Taplin
Venue: Proceedings of the 36th conference on Winter simulation (2004)

The optimizing sequence of production for a set of customer orders - in order to minimize machine set-up time and costs - is one of the typical problems found in many manufacturing systems. In this paper, we develop a simulation model to capture a practical system of a metal casting company in Queensland, Australia, and optimize the production sequence for a set of customer orders. The method addressed in the paper can be applied to other optimization problems in manufacturing industry.