ppxscal/embedding_network huggingface dataset:
The von Restorff Effect in Amnesia: The Contribution of the Hippocampal System to Novelty-Related Memory Enhancements
Authors: M. M. Kishiyama, A. P. Yonelinas, M. M. Lazzara
Venue: Journal of Cognitive Neuroscience (2004)

The ability to detect novelty is a characteristic of all mammalian nervous systems (Sokolov, 1963), and it plays a critical role in memory in the sense that items that are novel, or distinctive, are remembered better than those that are less distinct (von Restorff, 1933). Although several brain areas are sensitive to stimulus novelty, it is not yet known which regions play a role in producing novelty-related effects on memory. In the current study, we investigated novelty effects on recognition memory in amnesic patients and healthy control subjects. The control subjects demon strated better recognition for items that were novel (i.e., presented in an infrequent color), and this effect was found for both recollection and familiarity-based responses. However, the novelty advantage was effectively eliminated in patients with extensive medial temporal lobe damage, mild hypoxic patients expected to have relatively selective hippocampal damage, and in a patient with thalamic lesions. The results indicate that the human medial temporal lobes play a critical role in producing normal novelty effects in memory.
Computer simulated dense-random packing models as approach to the structure of porous low-k dielectrics
Authors: H. Hermann, A. Elsner, M. Hecker, D. Stoyan
Venue: Microelectronic Engineering (2005)

Nanoporous low-k dielectrics are simulated by means of the model of randomly packed hard spheres. The spheres and the space between them represent the pores and the solid material of the insulator, respectively. The generalisation of the model for arbitrary continuous distributions offers the opportunity to optimise the structures with respect to low k values. A local maximum of 70% porosity is obtained for a power-law pore size distribution with exponent -3.3. The elastic constants of the models are calculated for the isotropic case in the composite sphere assemblage approach. Results for the effective dielectric constant, the Young's modulus and the bulk and shear modulus are presented for the range of porosity up to 70%.
Geographical Cluster-Based Routing in Sensing-Covered Networks
Authors: Hannes Frey, Daniel Gorgen
Venue: IEEE Transactions on Parallel and Distributed Systems (2006)

The relationship between coverage and connectivity in sensor networks has been investigated in recent research treating both network parameters in a unified framework. It is known that networks covering a convex area are connected if the communication range of each node is at least twice a unique sensing range used by each node. Furthermore, geographic greedy routing is a viable and effective approach providing guaranteed delivery for this special network class. In this work, we will show that the result about network connectivity does not suffer from generalizing the concept of sensing coverage to arbitrary network deployment regions. However, dropping the assumption that the monitored area is convex requires the application of greedy recovery strategies like traversing a locally extracted planar subgraph. This work investigates a recently proposed planar graph routing variant and introduces a slight but effective simplification. Both methods perform message forwarding along the edges of a virtual overlay graph instead of using wireless links for planar graph construction directly. In general, there exist connected network configurations where both routing variants may fail. However, we will prove three theoretical bounds which are a sufficient condition for guaranteed delivery of these routing strategies applied in specific classes of sensing covered networks. By simulation results, we show that geographical cluster-based routing outperforms existing related geographical routing variants based on one-hop neighbor information. Furthermore, simulations performed show that geographical cluster-based routing achieves a comparable performance compared to variants based on two-hop neighbor information, while maintaining the routing topology consumes a significantly reduced amount of communication resources.
The Neural Substrates of Visual Implicit Memory: Do the Two Hemispheres Play Different Roles?
Authors: N. E. A. Kroll, A. P. Yonelinas, M. M. Kishiyama, K. Baynes, R. T. Knight, M. S. Gazzaniga
Venue: Journal of Cognitive Neuroscience (2003)

Identification of visually presented words is facilitated by implicit memory, or visual priming, for past visual experiences with those words. There is disagreement over the neuro-anatomical substrates of this form of implicit memory. Several studies have suggested that this form of priming relies on a visual word-form system localized in the right occipital lobe, whereas other studies have indicated that both hemispheres are equally involved. The discrepancies may be related to the types of priming tasks that have been used because the former studies have relied primarily on word-stem completion tasks and the latter on tasks like word-fragment completion. The present experiments compared word-fragment and word-stem measurements of visual implicit memory in patients with right occipital lobe lesions and patients with complete callosotomies. The patients showed normal visual implicit memory on fragment completion tests, but essentially no visual priming on standard stem completion tests. However, when we used a set of word stems that had only one correct solution for each test item, as was true of the items in the fragment completion tests, the patients showed normal priming effects. The results indicate that visual implicit memory for words is not solely dependent upon the right hemisphere, rather it reflects changes in processing efficiency in bilateral visual regions involved in the initial processing of the items. However, under conditions of high lexical competition (i.e., multiple completion word stems), the lexical processes, which are dominant in the left hemisphere, overshadow the visual priming supported by the left hemisphere.
An Investigation of Learning Style Differences and Attitudes toward Digital Game-based Learning among Mobile Users
Authors: Ching-Chiu Chao
Venue: Proceedings of the Fourth IEEE International Workshop on Wireless, Mobile and Ubiquitous Technology in Education (2006)

Game-based learning in mobile and ubiquitous learning environments has gained great interests in recent years throughout the world and there is every indication that the trend will continue. This paper is a brief report on the findings of a study conducted on student mobile users' learning style, attitudes toward game-based learning in mobile and ubiquitous learning environments and the relationship between learning styles and attitudes towards digital gamebased learning in this environment. Characteristics and principles of digital game-based learning, learning style based on experiential learning theory, constructivist learning approach to problem solving, interactions of collaborative learning, engagement of fun-flow experiences and characteristics of mobileubiquitous learning environments are synthesized as a framework to investigate research inquiries. This study provided insights for better understanding the design, theory and practice of game-based learning in mobileubiquitous environments.
BitTorrent Traffic Characteristics
Authors: David Erman, Dragos Ilie, Adrian Popescu
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2006)

This paper reports on a measurement and modeling study of session and message characteristics of BitTorrent traffic. BitTorrent is a Peer-to-Peer (P2P) replication and distribution system developed as an alternative to the classical client-server model to reduce the load on content servers and networks. Results are reported on measurement, modeling and analysis of application and link layer traces collected at the Blekinge Institute of Technology (BTH) and a local ISP in Sweden. Link layer traces and application logs were collected, modeled and analyzed using a dedicated measurement infrastructure developed at BTH to collect P2P traffic. New results are reported on important session and message characteristics of BitTorrent, i.e., session interarrivals, sizes and durations, request rates and response times. Our results show that session interarrivals can be accurately modeled by a second-order hyper-exponential distribution while session durations and sizes can be reasonably well modeled by various mixtures of the Log-normal and Weibull distributions. Response times have been observed to be modeled by a dual Log-normal mixture, while request rates are modeled as dual Gaussian distributions.
An Integrated System for Virtual Scene Rendering, Stereo Reconstruction and Accuracy Estimation.
Authors: J. G. Marichal-Hernandez, F. Perez Nava, F Rosa, R. Restrepo, J. M. Rodriguez-Ramos
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

This article depicts an integrated system capable of generating virtual stereo scenes, reconstructing a threedimensional map of distances, and calculating the accuracy of the results obtained. This tool is particularly useful for verifying the validity of distance reconstruction techniques, and is robust enough to use in a wide variety of scenarios since it avoids the need for an image-capture system in laboratory simulations. The importance of the distance reconstruction problem lies in the range of its applications: industrial inspection and quality control, surveillance and security, autonomous vehicles, robotic systems, medical image analysis, image databases, virtual reality, telepresence, and telerobotics. The system is based on the VRML standard for threedimensional geometric scene representation, on OpenGL for rendering virtual scenes, and on the TRW algorithm for the problem of three-dimensional reconstruction.
Patterns of Activity in the Categorical Representations of Objects
Authors: Thomas A. Carlson, Paul Schrater, Sheng He
Venue: Journal of Cognitive Neuroscience (2003)

Object perception has been a subject of extensive fMRI studies in recent years. Yet the nature of the cortical representation of objects in the human brain remains controversial. Analyses of fMRI data have traditionally focused on the activation of individual voxels associated with presentation of various stimuli. The current analysis approaches functional imaging data as collective information about the stimulus. Linking activity in the brain to a stimulus is treated as a pattern-classification problem. Linear discriminant analysis was used to reanalyze a set of data originally published by Ishai et al. (2000), available from the fMRIDC (accession no. 2-2000-1113D). Results of the new analysis reveal that patterns of activity that distinguish one category of objects from other categories are largely independent of one another, both in terms of the activity and spatial overlap. The information used to detect objects from phase-scrambled control stimuli is not essential in distinguishing one object category from another. Furthermore, performing an object-matching task during the scan significantly improved the ability to predict objects from controls, but had minimal effect on object classification, suggesting that the task-based attentional benefit was non-specific to object categories.
Epitaxial nanostructures assembled on InSb(001) by submonolayer deposition of gold
Authors: M. Goryl, J. J. Kolodziej, F. Krok, P. Piatkowski, B. Such, M. Szymonski
Venue: Microelectronic Engineering (2005)

Nanostructures formed during submonolayer deposition of gold on clean c(8x2)InSb(001) surface in ultrahigh vacuum have been investigated with dynamic force microscopy (DFM) and Kelvin probe force microscopy (KPFM). It is found that gold structures have predominantly the form of rectangular islands with edges oriented along and directions and their average size is dependent on the substrate temperature during evaporation. Upon annealing the initial rectangular shape of the islands is preserved but their average size is almost doubled. Furthermore, KPFM chemical imaging of the islands evidences that their composition is different from the composition of the homogeneous substrate. In addition, the change of the low energy electron diffraction pattern from c(8x2) to c(4x4) strongly suggests that the substrate surface between the islands has been converted from In-rich to Sb-rich, most likely due to alloying of the surface indium with gold in the islands.
Application of idea of chaos control to stabilization of stationary generation in backward-wave oscillator
Authors: A. M. Dolov, S. P. Kuznetsov
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

The method of suppression of self-modulation in a backward wave tube is offered. For this, the additional circuit of a delayed feedback is introduced in such way that the level of amplitude of output signal influences magnitude of a current of electron beam at the input of the interaction space. Results of numerical simulation demonstrate a possibility to increase working current twice, keeping a single-frequency regime of generation.
Multipath profile discrimination in TOA-based WLAN ranging with link layer frames
Authors: Marc Ciurana, Francisco Barceló, Sebastiano Cugno
Venue: Proceedings of the 1st international workshop on Wireless network testbeds, experimental evaluation characterization (2006)

Indoor ranging and location in WLAN is possible through obtaining Round-Trip-Time (RTT) measurements at data link level. This procedure allows using the existing IEEE 802.11 WLAN infrastructure with minor changes in order to provide an accurate estimation of the position of the mobile terminal. In this paper, an approach to overcome the undesired impact of the indoor radio-channel multipath on the accuracy of the TOA estimation between the terminal and an Access Point is presented. Ranging errors caused by multipath are quantified for different channel profiles: Dominant Direct Path (DDP), Non Dominant Direct Path (NDDP) and Undetectable Direct Path (UDP). However, the main challenge corresponds to be able to identify this profile (i.e. the multipath condition) from the obtained RTT measurements at IEEE 802.11 link level. This allows applying a TOA estimation algorithm sensitive to the detected profile in order to minimize the TOA estimation error.
Time Scaling Property on Edge Routers
Authors: Takuo Nakashima
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Accurate traffic model is crucial for network applications. Delay and its second measures, i.e. jitter, represent network activity and compose the function to assess the traffic model. In this paper, we show time scaling analysis for jitter on different type of edge routers based on wavelet scaling analysis. After collecting the actual data using our implemented path based active measurement method, following results are extracted. Firstly, the edge router from LAN to WAN diverse average energies to different values. Secondly, the property of average energy propagates through the path even if local return process operates heavily on the middle of the path. Thirdly, the exchanging point between providers raises average energy caused not only by local return element but also by forwarding and backwarding elements. Finally, bandwidth restriction between Japan and the U.S. slightly increases jitter fluctuations.
The R-CUBE: Reviewing, Reinforcing and Rewarding after SuccessfulModule Completion
Authors: Ciaran O'Leary
Venue: Proceedings of the 19th Conference on Software Engineering Education and Training Workshops (2006)

Revisiting material previously presented and successfully assessed can lead to much frustration among teaching staff and students. Despite this, it is often a requirement due to the time lag between the point at which a student begins a module and the time when they successfully passed a prerequisite module. Also, students who successfully pass a module fit into a number of categories, from those who were successful in all components of the assessment to those who displayed the minimum level of competence required for satisfaction of the learning outcomes. We introduce a novel instructional model which we predict will be instrumental in assisting our undergraduate Software Engineers who have displayed medium levels of competence in passing practical modules. The R-CUBE recognizes the importance of three dimensions to revisiting material - review, reinforce and reward. Our initial implementation of instruction using the model employs novel teaching and learning methods closely tied to our experience with service learning projects. We expect to fully evaluate the effectiveness of the model when the first students pass through a project that employs it at the end of this academic year.
Shape Similarity Index for Time Series based on Features of Euclidean Distances Histograms
Authors: E. Bautista-Thompson, S. Santos De la Cruz
Venue: Proceedings of the 15th International Conference on Computing (2006)

Shape similarity between time series is quantified based on descriptive statistical features from histograms of Euclidean distances. The histogram shows the statistical distribution of point to point differences between two time series, using this representation of the compared time series, a shape similarity index was designed. The index quantifies the differences between histograms with respect to an ideal similarity histogram that corresponds to a reference time series, this index allows the ordering of a set of time series based on their similarity with respect to this time series. A benchmark set of time series with known similarities and dissimilarities was used in order to evaluate the performance of the proposed index. The experimental results show that this index is able to order and differentiate with good resolution the time series, by their similarity with respect to the reference time series.
A Refractive Camera for Acquiring Stereo and Super-resolution Images
Authors: Chunyu Gao, Narendra Ahuja
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

We propose a novel depth sensing system composed of a single camera, and a transparent plate which is placed in front of the camera and rotates about the optical axis of the camera. The camera takes a sequence of images as the plate rotates, which provide the equivalent of a large number of stereo pairs. Compared with conventional multi-camera stereo systems, the use of a single camera for capturing stereo pairs helps improve the accuracy of detecting correspondences. The availability of the large number of stereo pairs also reduces matching ambiguities, even for objects with low texture. By using both the images and the estimated depth map, we show that the proposed system is also capable of generating super-resolution images. Experimental results on reconstructing 3D structures and recovering highresolution images are presented.
Reducing costly information acquisition in auctions
Authors: Kate Larson
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Most research on auctions assumes that potential bidders have private information about their willingness to pay for the item being auctioned, and that they use this information strategically when formulating their bids. In reality, bidders often have to go through a costly information-gathering process in order to learn their valuation for the item being auctioned. Recent attempts at modelling this phenomena has brought to light complex strategic behavior arising from information-gathering, and has shown that traditional approaches to auction and mechanism design are not able to overcome it. In this paper, we show that if the auction designer has some information about the agents' information-gathering processes, then it is possible to create an auction where, in equilibrium, agents have incentive to only gather information on their own valuation problems and to reveal the results truthfully to the auctioneer. Additionally, simulation results show that, from a system-level perspective, the overall cost of information acquisition is substantially lower in this new auction when it is compared to a classic auction mechanism.
Learning Top-Down Grouping of Compositional Hierarchies for Recognition
Authors: Bjorn Ommer, Michael Sauter, Joachim M. Buhmann
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

The complexity of real world image categorization and scene analysis requires compositional strategies for object representation. This contribution establishes a compositional hierarchy by first performing a perceptual bottom-up grouping of edge pixels to generate salient contour curves. A subsequent recursive top-down grouping yields a hierarchy of compositions. All entities in the compositional hierarchy are incorporated in a Bayesian network that couples them together by means of a shape model. The probabilistic model underlying top-down grouping as well as the shape model is learned automatically from a set of training images for the given categories. As a consequence, compositionality simplifies the learning of complex category models by building them from simple, frequently used compositions. The architecture is evaluated on the highly challenging Caltech 101 database1 which exhibits large intra-category variations. The proposed compositional approach shows competitive retrieval rates in the range of 53 .0 ± 0 .49%.
The Function Space of an Activity
Authors: Ashok Veeraraghavan, Rama Chellappa Amit K. Roy-Chowdhury
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

An activity consists of an actor performing a series of actions in a pre-defined temporal order. An action is an individual atomic unit of an activity. Different instances of the same activity may consist of varying relative speeds at which the various actions are executed, in addition to other intra- and inter- person variabilities. Most existing algorithms for activity recognition are not very robust to intra- and inter-personal changes of the same activity, and are extremely sensitive to warping of the temporal axis due to variations in speed profile. In this paper, we provide a systematic approach to learn the nature of such time warps while simultaneously allowing for the variations in descriptors for actions. For each activity we learn an 'average' sequence that we denote as the nominal activity trajectory. We also learn a function space of time warpings for each activity separately. The model can be used to learn individualspecific warping patterns so that it may also be used for activity based person identification. The proposed model leads us to algorithms for learning a model for each activity, clustering activity sequences and activity recognition that are robust to temporal, intra- and inter-person variations. We provide experimental results using two datasets.