ppxscal/embedding_network huggingface dataset:
The influence of spatial delocation on perceptual integration of vision and touch
Authors: Marco Congedo, Anatole Lécuyer, Edouard Gentaz
Venue: Presence: Teleoperators and Virtual Environments (2006)

How do we perceive objects when what we see and what we touch is not at the same place? In a virtual environment, we observed that spatial delocation promotes visual dominance when judging the rotation angle of a hand-operated handle. Thus, the delocation of perceptual information appears to increase considerably the weight of the dominant sense at the expense of the other. We relate this result to the design of teleoperation and virtual reality systems, in which, typically, the visual and haptic sensory information originates in spatially distinct devices.
fMRI Evidence for the Role of Recollection in Suppressing Misattribution Errors: The Illusory Truth Effect
Authors: Jason P. Mitchell, Chad S. Dodson, Daniel L. Schacter
Venue: Journal of Cognitive Neuroscience (2005)

Misattribution refers to the act of attributing a memory or idea to an incorrect source, such as successfully remembering a bit of information but linking it to an inappropriate person or time [Jacoby, L. L., Kelley, C., Brown, J., & Jasechko, J. (1989). Becoming famous overnight: Limits on the ability to avoid unconscious influences of the past. Journal of Personality and Social Psychology, 56, 326&ndash;338; Schacter, D. L. (1999). The seven sins of memory: Insights from psychology and cognitive neuroscience. American Psychologist, 54, 182&ndash;203; Schacter, D. L. (2001). The seven sins of memory: How the mind forgets and remembers. Boston: Houghton Mifflin]. Cognitive studies have suggested that misattribution errors may occur in the absence of recollection for the details of an initial encounter with a stimulus, but little is known about the neural basis of this memory phenomenon. Here we used functional magnetic resonance imaging (fMRI) to examine the hypothesized role of recollection in counteracting the illusory truth effect, a misattribution error whereby perceivers systematically overrate the truth of previously presented information. Imaging was conducted during the encoding and subsequent judgment of unfamiliar statements that were presented as true or false. Event-related fMRI analyses were conditionalized as a function of subsequent performance. Results demonstrated that encoding activation in regions previously associated with successful recollection&mdash;including the hippocampus and the ventrolateral prefrontal cortex (PFC)&mdash;correlated with the successful avoidance of misattribution errors, providing initial neuroimaging support for earlier cognitive accounts of misattribution.
Small World Architecture for Peer-to-Peer Networks
Authors: Lu Liu, Stephen Mackin, Nick Antonopoulos
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

Small-world phenomenon has been observed in existing peer-to-peer (P2P) networks, such as Gnutella and Freenet. Due to the similarity of P2P networks to social networks, the previous small-world model proposed by Duncan Watts can be adopted in the design of P2P networks: each node is connected to some neighbouring nodes, and a group of nodes keep a small number of long links to randomly chosen distant nodes. Unfortunately, current unstructured search algorithms have difficulty distinguishing these random long-range shortcuts. This paper presents small world architecture for P2P networks (SWAN) with a semi-structured P2P search algorithm that is used to create and find long-range shortcuts toward remote peer groups. In SWAN, not every peer node needs to be connected to remote groups, but every peer node can easily find which peer nodes have external connections to a specific peer group.
Generating Rewrite Rules by Browsing RDF Data
Authors: Ora Lassila
Venue: Proceedings of the Second International Conference on Rules and Rule Markup Languages for the Semantic Web (2006)

In this paper we show how path queries in the WILBUR query engine can be augmented via the use of a simple rule system. This system can substitute atomic query expressions with complex queries, effectively rewriting queries. We demonstrate that this approach can be used for simple reasoning in the context of RDF(S). We further present a tool that allows the user to create complex queries merely by browsing an RDF graph, and by virtue of naming the automatically generated queries can create rules for the rule system. These rules appear in the system as "virtual" RDF properties, and enable the user to interactively customize how RDF data is presented.
Modified predictive line search for block motion estimation on multimedia processors
Authors: Shih-Yu Huang
Venue: Signal Processing (2006)

Predictive line search (PLS) algorithm had already been approved successfully in block motion estimation on multimedia processors to take the advantages of flexibility and parallelism. This paper presents an efficient algorithm named modified PLS (MPLS) to avoid redundant computation of PLS. In addition, MPLS utilizes an adaptive computation distribution mechanism to efficiently allocate the available computation of the employed multimedia processors to blocks or frames of video sequences to achieve higher output quality. Dependent on the motion activity in videos, experimental results indicate that MPLS performs better than PLS in terms of output quality and requires less computation by up to 23% on average.
Dynamic Learning Need Reflection System for Academic Education and Its Applicability to Intelligent Agents
Authors: Yoshitaka Sakurai, Shinichi Dohi, Shogo Nakamura, Setsuo Tsuruta, Rainer Knauf
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

A new concept DLNR (Dynamic Learning Need Reflection) and its system used in the education at a university are suggested. The effects, particularly on the learning of software agents, are analyzed. DLNR's goal is to increase students' learning motivation through dynamically clarifying and reflecting their learning need. To attain this, DLNR includes "prerequisite conditions", "no compulsory subjects", "payment for each subject" and "Grade Point Average: GPA" to estimate learning results. By using a tool to realize DLNR, students design their learning need, namely their graduation timeline, by themselves to achieve their academic goal towards their job after graduation. Through taking classes, students dynamically modify the timeline reflectively according to the intermediate results shown by GPA. DLNR's effects are evaluated. Particularly, DLNR was found applicable to the learning of software agents for intelligent system assistants, through incorporating more general tools such as Storyboard.
Discrete-time H∞ filtering with initial condition
Authors: Y. K. Foo
Venue: International Journal of Systems Science (2005)

We consider the problem of finite horizon discrete time H∞ filtering with uncertain initial condition. An H∞ norm-like performance measure that explicitly accounts for the effect of the initial condition is proposed. Conditions are then derived for the existence and construction of a strictly causal sub-optimal estimator that achieves a pre-specified value of this performance measure. It is also shown that the achievable infimum value of this measure would in general depend on the structure and magnitude of uncertainty present in the initial condition of the system.
Mutual enrichment through nested belief change
Authors: Laurent Perrussel, Jean-Marc Thévenin, Thomas Meyer
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

We investigate the dynamics of nested beliefs in the context of agent interactions. Nested beliefs represent what agents believe about the beliefs of other agents. We consider the tell KQML performative which allows agents to send their own beliefs to others. Whenever agents accept a new belief, or refuse to change their own beliefs after receiving a message, both receiver and sender enrich their nested beliefs by refining their beliefs about the other agent's beliefs, as well as the preferences of the other agent. The main objective of nested beliefs is to improve cooperation between agents. We propose a logical framework for the acquisition process of nested beliefs and preferences. This acquisition process is the first step toward the elaboration of sophisticated interaction protocols. In this short paper we provide an informal outline of the framework, guided by an intuitive running example.
Development and evaluation of an enhanced weighted frequency fourier linear combiner algorithm using bandwidth information
Authors: J. Robert Boston
Venue:  (2006)

Driving an electric powered wheelchair with a joystick is a complex task for the user who has a pathological tremor. Most powered wheelchairs use simple filtering algorithms to reduce the effects of tremor. These algorithms work well in most situations, but fall short in others. This study addresses the problems associated with pathological tremor associated with Cerebral Palsy (CP). The purpose of this study is to know more about the characteristics of CP tremor with time-frequency analysis and to improve joystick control with other advanced filtering algorithms. We used three estimated parameters, instantaneous frequency (IF), instantaneous bandwidth (IB), and instantaneous power (IP), from a time-frequency distribution (TFD), to characterize CP tremor and to tune a notch filter for canceling CP tremor noise from a joystick signal in an off-line experiment. From the off-line experiment, we showed that our CP tremor suppression system performed better with the information of IF, IB, and IP. We also conducted an on-line experiment in which we introduced two tremor suppression algorithms. One is Weighted-frequency Fourier Linear Combiner (WFLC), which estimates a tremor frequency and its weight, and the other is our modified WFLC, which adjusts a notch width with respect to the bandwidth of CP tremor additionally. We implemented both algorithms on the virtual wheelchair driving test along with a commonly used low-pass filter. We recruited ten subjects who have CP tremor and tested them in a virtual wheelchair driving environment. We observed that CP tremors in the joystick signal were suppressed greatly by the new filtering algorithms. We learned that the time-delay of a low-pass filter caused serious performance degradation of wheelchair driving and observed that most subjects performed better with new filtering methods than with a low-pass filter. Furthermore, since our modified WFLC algorithm was able to reduce more CP tremor noise than WFLC, we learned that it is important to consider the bandwidth information of CP tremor when designing a tremor suppression system.
Joint modeling and analysis using XMSF web services
Authors: Arnold Buss, John Ruck
Venue: Proceedings of the 36th conference on Winter simulation (2004)

This paper describes the creation of a new analytical modeling capability by bringing together the Naval Simulation System (NSS) for sea strike and COMBATXXI for littoral and land warfare modeling. The models are linked by Web services using principles from the Extensible Modeling and Simulation Framework (XMSF). This implementation is an exemplar for a transformational framework for design, development, and integration of simulation models.
Robust approximate likelihood ratio tests for nonlinear dynamic systems
Authors: L. B. White
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

The paper addresses the problem of determining which one of a finite number of nonlinear dynamic systems generated a given noisy measured signal. An approximate likelihood ratio test (LRT) is proposed which consists of bank of an extended Kalman filters (EKFs) each tuned to one of the candidate signal models. The prediction error sequences of each EKF are used to form the LRT since each is nominally approximately zero-mean Gaussian with known covariance if it matches the measured signal. The Gaussian approximation is good at high signal-to-noise ratios (SNRs) but can degrade rapidly as the SNR decreases. The paper proposes a robustification of the test which is based on Huber's (1965) robust LRTs.
Blood Vessel Detection via a Multi-window Parameter Transform
Authors: Katia Estabridis, Rui Defigueiredo
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

A parallel algorithm to detect retinal blood vessels has been developed for use in an automated diabetic retinopathy detection system. Localized adaptive thresholding and a multi-window Radon transform (RT) are utilized to detect the vascular system in retinal images. Multi-window parameter transforms are intrinsically parallel and offer increased performance over conventional transforms. The image is adaptively thresholded and then the multi-window RT is applied at different window sizes partition levels. Results from each partition level are combined and morphologically processed to improve final performance. Multiple partitions are necessary to account for the size variation present in retinal blood vessels. The algorithm was tested with 20 images, 10 normal and 10 abnormal and the results demonstrate the robustness of the algorithm in the presence of noise. An average true positive rate of 86.3% with a false positive rate of 3.9% is accomplished with this algorithm when tested against hand-labeled data.
Feature Extraction Using Information-Theoretic Learning
Authors: Kenneth E. Hild, Deniz Erdogmus, Kari Torkkola Jose C. Principe
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

A classification system typically consists of both a feature extractor (preprocessor) and a classifier. These two components can be trained either independently or simultaneously. The former option has an implementation advantage since the extractor need only be trained once for use with any classifier, whereas the latter has an advantage since it can be used to minimize classification error directly. Certain criteria, such as Minimum Classification Error, are better suited for simultaneous training, whereas other criteria, such as Mutual Information, are amenable for training the feature extractor either independently or simultaneously. Herein, an information-theoretic criterion is introduced and is evaluated for training the extractor independently of the classifier. The proposed method uses nonparametric estimation of Renyi's entropy to train the extractor by maximizing an approximation of the mutual information between the class labels and the output of the feature extractor. The evaluations show that the proposed method, even though it uses independent training, performs at least as well as three feature extraction methods that train the extractor and classifier simultaneously.
The hats simulator
Authors: Paul R. Cohen, Clayton T. Morrison
Venue: Proceedings of the 36th conference on Winter simulation (2004)

The Hats Simulator is designed to be a lightweight proxy for many intelligence analysis problems, and thus a test environment for analysts' tools. It is a virtual world in which many agents engage in individual and collective activities. Most agents are benign, some intend harm. Agent activities are planned by a generative planner. Playing against the simulator, the job of the analyst is to find harmful agents before they carry out their plans. The simulator maintains information about all agents. However, information is hidden from the analyst and some is expensive. After each game, the analyst is assessed a set of scores including the cost of acquiring information about agents, the cost of falsely accusing benign agents, and the cost of failing to detect harmful agents. The simulator is implemented and currently manages the activities of up to one hundred thousand agents.
Public domain software: part II
Authors: Elliot S. Wheeler
Venue: ACM SIGSMALL Newsletter (1984)

Public domain software is a large collection of software in the public domain and available to individuals for their own use for very minimal costs. There is more than 40 megabytes of this material easily available to almost any user of a microcomputer. The programs are written in many languages. Source and original documentation are often present. The subject matters covered range from machine dependent games to implementations of complete language systems and data bases. They are usually distributed on single density 8 inch floppy diskettes, using standard IBM 3740 format, for Digital Research's CP/M operating system or one of its look-alikes or successors. There are occasional limitations on the commercial use of these programs, but I understand that there is no limitation on their non-commercial use. 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
Supporting Modularization and Aggregation of Learning Resources in a SCORM Compliance Mode
Authors: Marek Meyer, Christoph Rensing, Ralf Steinmetz
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Modular Learning Resources that can be aggregated to larger Learning Resources are crucial for the future success of E-Learning. Re-use of Learning Resources will only reach significant numbers, if not only re-use "as-is" is supported, but also aggregation and adaptation to a new teaching or learning context. This paper analyzes requirements on a format for Learning Resources that supports modularization and aggregation. A suitable format based on SCORM and LOM is proposed and afterwards evaluated by means of a tool implementation.
A learning journey in problem-based learning
Authors: Jennifer Yeo, Seng Chee Tan, Yew-Jin Lee
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

This ethnographic case study describes what happened when a high school biology teacher in Singapore adopted problem-based learning (PBL). Using activity theory, we compare her instructional unit with a reference PBL model derived from the literature. We found disparities in the motives driving these two activity systems, which we attribute to differences between the lived-realities of practitioners and academics. As the researchers collaborate with practitioners through joint reflective practices, our goal is to work towards an equilibrium point whereby PBL could be implemented meaningfully and realistically in an Asian society that has long placed a premium on academic achievement.
Adaptive Binary Trees Visualization with Respect to User-Specified Quality Measures
Authors: Adrian Rusu, Christopher Clement, Radu Jianu
Venue: Proceedings of the conference on Information Visualization (2006)

Many algorithms have been designed to visualize binary trees efficiently with respect to a quality measure. While each algorithm is suitable for drawing particular categories of binary trees, an effort to compile these algorithms to maximize the quality of drawings has not been realized. Our first step is to create a system that determines the type of a binary tree and then selects an algorithm to draw the tree depending upon the specified quality measures. Currently, our system recognizes six types of binary trees (AVL, Complete, Fibonacci, Random, Unbalanced-tothe- left, Unbalanced-to-the-right) and allows the user to choose from eleven quality measures (Area, Aspect Ratio, Total Edge Length, Maximum Edge Length, Uniform Edge Length, Closest Leaf, Farthest Leaf, Size, Minimum Angle Size, Average Angle Size, Angular Resolution). Experiments show that our adaptive visualization system outperforms any system using a single binary tree drawing algorithm. In addition, our approach allows the user to select multiple quality measures and automatically detects the best available binary tree drawing algorithm.
The State of the Magazine
Authors: James Hendler
Venue: IEEE Intelligent Systems (2006)

James Hendler looks back at his first two years as editor in chief.
1-Fair Alternator Designs for the de Bruijn Network
Authors: Hsu-Shen Lin, Chang-Biau Yang, Kuo-Tsung Tseng
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

In a 1-fair alternator of a network of concurrent processors, no processor executes the critical step twice when one or more other processors have not executed the critical step yet. In this paper, two algorithms are proposed to solve the coloring (1-fair alternator design) problem on the de Bruijn network. The first one uses 2\left\lceil {\log _n k} \right\rceil +1 colors to color the k-ary de Bruijn graph with two digits, while the second one uses p + 1 only colors, where \left( {\mathop {p - 1}\limits_{\left\lfloor {(p - 1)/2} \right\rfloor } } \right) \le k \leqslant \left( {\mathop p\limits_{\left\lfloor {p/2} \right\rfloor } } \right). The second coloring method is optimal when k = \left( {\mathop p\limits_{\left\lfloor {p/2} \right\rfloor } } \right). Furthermore, the extension of our coloring method can be applied to the k-ary de Bruijn graph with three or more digits.
Fuzzy methods for case-based recommendation and decision support
Authors: Didier Dubois, Eyke Hüllermeier, Henri Prade
Venue: Journal of Intelligent Information Systems (2006)

The paper proposes two case-based methods for recommending decisions to users on the basis of information stored in a database. In both approaches, fuzzy sets and related (approximate) reasoning techniques are used for modeling user preferences and decision principles in a flexible manner. The first approach, case-based decision making, can principally be seen as a case-based counterpart to classical decision principles well-known from statistical decision theory. The second approach, called case-based elicitation, combines aspects from flexible querying of databases and case-based prediction. Roughly, imagine a user who aims at choosing an optimal alternative among a given set of options. The preferences with respect to these alternatives are formalized in terms of flexible constraints, the expression of which refers to cases stored in a database. As both types of decision support might provide useful tools for recommender systems, we also place the methods in a broader context and discuss the role of fuzzy set theory in some related fields.
Performance of optimized software implementation of the iSCSI protocol
Authors: Fujita Tomonori, Ogawara Masanori
Venue: Proceedings of the international workshop on Storage network architecture and parallel I/Os (2003)

The advent of IP-based storage networking has brought specialized network adapters that directly support TCP/IP and storage protocols on the market to get comparable performance that specialized high-performance storage networking architectures provide.This paper describes an efficient software implementation of the iSCSI protocol with a commodity networking infrastructure. Though several studies have compared the performances of specialized network adapters and commodity network adapters, our iSCSI implementation eliminates data copying overhead unlike straightforward iSCSI implementations used in previous studies. To achieve it, we modified a general-purpose operating system by using techniques studied for improving TCP performance in the literature and features that commodity Gigabit Ethernet adapters support. We also quantified their effects.Our microbenchmarks show, compared with a straightforward iSCSI driver that does not use these techniques, the iSCSI driver with these optimizations reduces CPU utilization from 39.4% to 30.8% when writing with an I/O size of 64 KB. However, when reading, any performance gain is negated due to the high cost of operations on the virtual memory system.