ppxscal/embedding_network huggingface dataset:
Summarizing Image/Surface Registration for 6DOF Robot/Camera Pose Estimation
Authors: Elisabet Batlle, Carles Matabosch, Joaquim Salvi
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

In recent years, 6 Degrees Of Freedom (DOF) Pose Estimation and 3D Mapping is becoming more important not only in the robotics community for applications such as robot navigation but also in computer vision for the registration of large surfaces such as buildings and statues. In both situations, the robot/camera position and orientation must be estimated in order to be used for further alignment of the 3D map/surface. Although the techniques differ slightly depending on the application, both communities tend to solve similar problems by means of different approaches. This article is a guide for any scientist interested in the field since the surveyed techniques have been compared pointing out their pros and cons and their potential applications.
Route Optimization with MAP-Based Enhancement in Mobile Networks
Authors: Jeonghoon Park, Tae-Jin Lee, Hyunseung Choo
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The development of wireless network technology and user demands for mobility support have motivated the IETF to introduce mobile IP, mobile IPv6, and its extension, the network mobility (NEMO) basic support protocol. In the NEMO environment, mobile networks form a nested structure. Nested mobile networks based on NEMO basic support (NBS) protocol have the pinball routing problem because packets are routed to all home agents of the mobile routers using nested tunnelling. In this paper, a route optimization scheme is proposed which uses the mobility anchor point employed in hierarchical mobile IPv6, and modifies the binding update messages to minimize overhead in route optimization. We evaluate route optimization cost in terms of delay. The results demonstrate a minimum performance improvement of 30% and even shorter routing delay than NBS in non-optimized cases.
Discovering Structure in the Space of Activation Profiles in fMRI
Authors: Danial Lashkari, Ed Vul, Nancy Kanwisher, Polina Golland
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We present a method for discovering patterns of activation observed through fMRI in experiments with multiple stimuli/tasks. We introduce an explicit parameterization for the profiles of activation and represent fMRI time courses as such profiles using linear regression estimates. Working in the space of activation profiles, we design a mixture model that finds the major activation patterns along with their localization maps and derive an algorithm for fitting the model to the fMRI data. The method enables functional group analysis independent of spatial correspondence among subjects. We validate this model in the context of category selectivity in the visual cortex, demonstrating good agreement with prior findings based on hypothesis-driven methods.
Information Life Cycle, Information Value and Data Management
Authors: Rudolf Bayer
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

Data volumes grow extremely fast. Storage capacity and cost can easily cope with that growth, but data access is critical. However, most information has a surprisingly short life cycle. This has a deep impact on data management systems and leads to a new storage architecture consisting of the two subsystems FileCache and FileStore with many advantageous properties w.r. to reliability, availability and cost. A multidimensional database of metadata is used to organize the data. This architecture is also suitable for complete multimedia biographies.
Efficient Management of Complex Striped Files in Active Storage
Authors: Juan Piernas, Jarek Nieplocha
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Active Storage provides an opportunity for reducing the bandwidth requirements between the storage and compute elements of current supercomputing systems, and leveraging the processing power of the storage nodes used by some modern file systems. To achieve both objectives, Active Storage allows certain processing tasks to be performed directly on the storage nodes, near the data they manage. However, Active Storage must also support key requirements of scientific applications. In particular, Active Storage must be able to support striped files and files with complex formats (e.g., netCDF). In this paper, we describe how these important requirements can be addressed. The experimental results on a Lustre file system not only show that our proposal can reduce the network traffic to near zero and scale the performance with the number of storage nodes, but also that it provides an efficient treatment of striped files and can manage files with complex data structures.
The roles of personality and class size in student attitudes toward individual response technology
Authors: Matthew Hunsinger, Christopher R. Poirier, Robert S. Feldman
Venue: Computers in Human Behavior (2008)

The use of individual response technology (IRT) in college classrooms is becoming increasingly common. In order to understand why some students enjoy IRT use whereas others do not, we examined the relationship between personality and attitudes towards IRT use in large and small classrooms. In addition, we investigated the relationship between IRT use and classroom learning. We collected data from 452 undergraduate students (209 males and 243 females). The results show that students who are more extraverted and conscientious report more positive ratings of IRT. Furthermore, students who earn higher grades enjoy IRT use more than other students. Implications for the effective use of IRT in the classroom are discussed and future directions for research are suggested.
On Path-Centric Navigation and Search Techniques for Personal Knowledge Stored in Topic Maps
Authors: Jens Heider, Julian Schütte
Venue: Scaling Topic Maps: Third International Conference on Topic Maps Research and Applications, TMRA 2007 Leipzig, Germany, October 11-12, 2007 Revised Selected Papers (2008)

Leveraging interconnections across stored personal information is a novel concept to find desired information by context and structure. This paper introduces a combined navigation and search interface for homogeneous knowledge representations based on path and set calculation. It uses graph theory to provide a more intuitive way of supplying search criteria and retrieving related information.
A Neural Network Generating Adaptive Rhythms for Controlling Behavior Based Robotic Systems
Authors: Ernesto Burattini, Silvia Rossi, Massimo De Gregorio
Venue: Proceedings of the 2008 10th Brazilian Symposium on Neural Networks (2008)

Influenced by the results obtained in neuroscience and biology, we have introduced a model (AIRM) that, inspired by biological rhythms, adaptively controls a behavior based robotic system (BBRS). The proposed model is implemented by means of an NSP (Neuro Symbolic Processor). Since the NSP can be implemented on FPGA, we can take advantage of a parallel execution of the AIRM model and then an improvement of the BBRS performance.
Load Shedding in MavStream: Analysis, Implementation, and Evaluation
Authors: Balakumar Kendai, Sharma Chakravarthy
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

In data stream management systems (DSMSs), Quality of Service (or QoS) requirements, as specified by users, are extremely important. To satisfy QoS requirements throughout the life of a data stream, result characteristics need to be monitored at runtime and adjustments made continuously. It has been shown that in a DSMS, switching scheduling strategies at runtime can change tuple latency requirements. DSMSs also experience significant fluctuations in input rates (termed bursty inputs). In order to meet the QoS requirements in the presence of bursty inputs, a load shedding strategy is critical. This also entails monitoring of QoS measures at run-time to meet expected QoS requirements.This paper addresses load shedding issues for MavStream, a DSMS being developed at UT Arlington. To cope with situations where the arrival rates of input streams exceed the processing capacity of the system, we have incorporated load shedders into the query processing model. The runtime optimizer continually monitors the output and decides when to turn on the shedders and how much to shed. Choice of shedders is done to minimize the error in the output. Shedders have been incorporated as part of the buffers to minimize the overhead for load shedding. Finally, load shedders are activated and deactivated dynamically by the runtime optimizer. Both random and semantic load shedding techniques are supported to match application semantics.
ARM: An Account-Based Hierarchical Reputation Management System for Wireless Ad Hoc Networks
Authors: Haiying Shen, Ze Li
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

Mobile ad hoc networking works properly only if mobile nodes cooperate in routing. However, since wireless mobile nodes are usually constrained by limited power and computation resources, some selfish nodes may refuse to forward packets which are not of their direct interest. Most previous efforts counter this behavior by having each node keep a reputation table and exchanging the information with each other, and refusing to forward the packets of selfish nodes. Maintaining and exchanging information among individual mobile nodes in a dynamic environment consumes significant resources, and such a punishment method is not effective enough. This paper presents a novel Account-based hierarchical Reputation Management system (ARM) to avoid selfish nodes and encourage node cooperation. In order to save there source consumption of information exchange, ARM builds a hierarchical structure with low mobility nodes in the high level. These nodes constitute a locality-aware DHT for efficient reputation value collection and exchange. %the storage and computing burden of the mobile nodes. Furthermore, ARM provides a novel account management model to encourage node cooperation in the network. The account management model intelligently integrates global reputation management reputation system and pricing-based model for effective selfish node punishment. Theoretical analysis and simulation results show that ARM can greatly improve the performance of a defenseless network by effectively deterring selfish nodes and encouraging node cooperation at a significantly low resource consumption.
Confluence by Decreasing Diagrams
Authors: Vincent Oostrom
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

The decreasing diagrams technique is a complete method to reduce confluence of a rewrite relation to local confluence. Whereas previous presentations have focussed on the proof the technique is correct, here we focus on applicability. We present a simple but powerful generalisation of the technique, requiring peaks to be closed only by conversions instead of valleys, which is demonstrated to further ease applicability.
The shape of an instant: measuring and modeling perceptual attack time with probability density functions (if a tree falls in the forest, when did 57 people hear it make a sound?)
Authors: Chris Chafe
Venue:  (2008)

A sound's Perceptual Attack Time ("PAT") is its perceived moment of rhythmic placement. PAT is notoriously difficult to measure, because all methods measure a test sound's PAT in relationship to an action or second sound, which add uncertainty to the measurements. This work uses the ideal impulse, which is an ideal reference because it is perfectly isolated in time with a very clear attack. However, its perfectly broad frequency spectrum is problematic because it is harder to perceive the relative timing of sounds when their spectra differ greatly. This motivates Spectrally Matched Click Synthesis, the creation of arbitrarily short clicks whose spectra approximate those of arbitrary input sounds. This work represents PAT as a function indicating the probability that a typical listener would hear the sound's PAT at each time, rather than as just one instant. The problem of deriving each sound's PAT from pairwise comparisons becomes one of estimating distributions of random variables for every sound's PAT given only observations of random variables corresponding to the difference two sounds' distributions plus noise. Methods to address this draw from maximum likelihood estimation and the shortest path problem. Subjects downloaded a listening test that presents a series of PAT measurement trials and allows them to adjust sounds' relative timing until they sound synchronous. This establishes perceptual "ground truth" for the PAT of a collection of 20 sounds compared against each other in various combinations. As hoped, subjects were able to align a sound more reliably to one of that sound's spectrally matched clicks than to other sounds of the same duration. The representation of PAT with probability density functions provides a new perspective on the problem of predicting PAT directly from acoustical signals. Rather than choosing a single moment for PAT given a segment of sound known a priori to contain a single musical event, these regression methods estimate continuous shapes of PAT distributions from continuous (not necessarily presegmented) audio signals, formulated as a supervised machine learning regression problem whose inputs are DSP functions computed from the sound. This work concludes with some preliminary musical applications of the resulting models.
Topic 3 Scheduling and Load-Balancing
Authors: Henri Casanova, Olivier Beaumont, Uwe Schwiegelshohn, Marek Tudruj
Venue: Proceedings of the 13th European international conference on Parallel Processing (2007)

While scheduling and load-balancing problems have been studied for several decades, the dramatic multi-scale shifts in distributed systems and their usage in the last few years have raised new and exciting challenges. These challenges span the entire spectrum from theory to practice, as demonstrated by the selection of papers in the scheduling and load-balancing topic this year at Europar. Out of the twenty-three submissions to the topic we accepted six papers. The topic organizers would like to thank all reviewers whose work made it possible for each paper to receive at least three reviews.
Using the Wizard of Oz Method to Train Persuasive Agents
Authors: Maiko Kawasoe, Tatsuya Narita, Yasuhiko Kitamura
Venue: Proceedings of the 12th international workshop on Cooperative Information Agents XII (2008)

Persuasive conversational agents persuade users to change their attitudes or behaviors through conversation and are expected to be applied as virtual sales-clerks in e-shopping sites. Developing such an agent requires a conversation model that identifies the most appropriate responses to the user's inputs. To create such a model, we propose the approach of combining a learning agent with the Wizard of Oz method; in this approach, a person (called the Wizard) talks to the user pretending to be the agent. The agent learns from the conversations between the Wizard and the user and constructs its own conversation model. In this approach, the Wizard has to reply to most of the user's inputs at the beginning, but the burden gradually falls because the agent learns how to reply as the conversation model grows.Every persuasive conversation has the goal of persuading the user and ends with success or failure. We introduce a goal-oriented conversation model that can represent the success probability of persuasion and a learning method to update the model depending on the success/failure of the persuasive conversation. We introduce a learning persuasive agent that implements the conversation model and the learning method and evaluate it in the situation wherein the agent persuades users to choose one type of digital camera over another. The agent could succeed in reducing the Wizard's inputs by 48%, and, more interestingly, succeeded in persuading 2 users without any help from the Wizard.
A Free-Roaming Mobile Agent Security Protocol Based on Anonymous Onion Routing and k Anonymous Hops Backwards
Authors: Xiaogang Wang, Darren Xu, Junzhou Luo
Venue: Proceedings of the 5th international conference on Autonomic and Trusted Computing (2008)

Security and anonymity are vital for free-roaming mobile agent-based applications. Based on anonymous onion routing, this paper proposes a security protocol to defend truncation attacks for free-roaming mobile agent-based applications. This protocol uses "two hops forwards and k anonymous hops backwards" chain relation to implement the generally accepted mobile agent security properties. Security analysis proves that this protocol can defend known attacks, especially multiple colluded truncation attacks and provide privacy protection to previously visited servers. Performance evaluation shows this protocol requires limited communication overhead if right parameters are chosen.
Superconvergence analysis of the SDFEM for elliptic problems with characteristic layers
Authors: S. Franz, T. Linß, H. -G. Roos
Venue: Applied Numerical Mathematics (2008)

In this paper we analyse the superconvergence property of the streamline diffusion finite element method (SDFEM) in the case of elliptic problems with characteristic layers. For the SDFEM we give optimal parameter choices for maximal stability in the induced streamline diffusion norm. It is shown that inside the parabolic boundary layer the SDFEM-parameter can be chosen of order @e^-^1^/^4N^-^2 which is also confirmed by numerical results.
Almost 2-SAT Is Fixed-Parameter Tractable (Extended Abstract)
Authors: Igor Razgon, Barry O'Sullivan
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

We consider the following problem. Given a 2-cnf formula, is it possible to remove at most k clauses so that the resulting 2-cnf formula is satisfiable? This problem is known to different research communities in theoretical computer science under the names Almost 2-SAT, All-but-k 2-SAT, 2-cnf deletion, and 2-SAT deletion. The status of the fixed-parameter tractability of this problem is a long-standing open question in the area of parameterized complexity. We resolve this open question by proposing an algorithm that solves this problem in O(15 k *k*m 3) time showing that this problem is fixed-parameter tractable.
A Receipt-Free Punch-Hole Ballot Electronic Voting Scheme
Authors: Han Wei, Zheng Dong, Chen Ke-fei
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

The punch-hole ballot electronic voting protocol is a special version of the e-voting paradigms based on homomorphic encryption. Assume that there are L candidates and a voter can select K distinct candidates, the punch-hole ballot is represented as a vector with L elements. The i-th entry of the ballot corresponds to the choice of the voter on the i-th candidate. The tallying authorities sum up components in respective locations of all votes to reveal the votes that are won by each pre-determined candidate. Receipt-freeness is an important security property to protect the election against vote buying and coercion. In this paper a receipt-free punch-hole ballot e-voting scheme is presented. A third party called "randomizer" is employed to re-encrypt the first ballot cast by the voter. The randomizer and the voter jointly generate the final ballot for the tally. Our scheme satisfies the requirements for cryptographic secure electronic voting protocols and is efficient for implementation.
Online Multiagent Learning against Memory Bounded Adversaries
Authors: Doran Chakraborty, Peter Stone
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

The traditional agenda in Multiagent Learning (MAL) has been to develop learners that guarantee convergence to an equilibrium in self-play or that converge to playing the best response against an opponent using one of a fixed set of known targeted strategies. This paper introduces an algorithm called Learn or Exploit for Adversary Induced Markov Decision Process (LoE-AIM) that targets optimality against any learning opponent that can be treated as a memory bounded adversary. LoE-AIM makes no prior assumptions about the opponent and is tailored to optimally exploit any adversary which induces a Markov decision process in the state space of joint histories. LoE-AIM either explores and gathers new information about the opponent or converges to the best response to the partially learned opponent strategy in repeated play. We further extend LoE-AIM to account for online repeated interactions against the same adversary with plays against other adversaries interleaved in between. LoE-AIM-repeated stores learned knowledge about an adversary, identifies the adversary in case of repeated interaction, and reuses the stored knowledge about the behavior of the adversary to enhance learning in the current epoch of play. LoE-AIM and LoE-AIM-repeated are fully implemented, with results demonstrating their superiority over other existing MAL algorithms.
Does Physical Security of Cryptographic Devices Need a Formal Study? (Invited Talk)
Authors: François-Xavier Standaert, Tal G. Malkin, Moti Yung
Venue: Proceedings of the 3rd international conference on Information Theoretic Security (2008)

Traditionally, cryptographic algorithms provide security against an adversary who has only black box access to cryptographic devices. That is, the only thing the adversary can do is to query the cryptographic algorithm on inputs of its choice and analyze the responses, which are always computed according to the correct original secret information. However, such a model does not always correspond to the realities of physical implementations.
Chances, Affordances, Niche Construction
Authors: Lorenzo Magnani
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

As a matter of fact, humans continuously delegate and distribute cognitive functions to the environment to lessen their limits. They build models, representations, and other various mediating structures, that are considered to aid thought. In doing these, humans are engaged in a process of cognitive niche construction. In this sense, I argue that a cognitive niche emerges from a network of continuous interplays between individuals and the environment, in which people alter and modify the environment by mimetically externalizing fleeting thoughts, private ideas, etc., into external supports. Through mimetic activities humans create external semiotic anchors that are the result of a process in which concepts, ideas, and thoughts are projected onto external structures. Once concepts and thoughts are externalized and projected, new chances and ways of inferring come up from the blend. For cognitive niche construction may also contribute to make available a great portion of knowledge that otherwise would remain simply unexpressed or unreachable.