ppxscal/embedding_network huggingface dataset:
The experience of enchantment in human&#x2013;computer interaction
Authors: John McCarthy, Peter Wright, Jayne Wallace, Andy Dearden
Venue: Personal and Ubiquitous Computing (2006)

Improving user experience is becoming something of a rallying call in human&#x2013;computer interaction but experience is not a unitary thing. There are varieties of experiences, good and bad, and we need to characterise these varieties if we are to improve user experience. In this paper we argue that enchantment is a useful concept to facilitate closer relationships between people and technology. But enchantment is a complex concept in need of some clarification. So we explore how enchantment has been used in the discussions of technology and examine experiences of film and cell phones to see how enchantment with technology is possible. Based on these cases, we identify the sensibilities that help designers design for enchantment, including the specific sensuousness of a thing, senses of play, paradox and openness, and the potential for transformation. We use these to analyse digital jewellery in order to suggest how it can be made more enchanting. We conclude by relating enchantment to varieties of experience.
Hardware support for spin management in overcommitted virtual machines
Authors: Philip M. Wells, Koushik Chakraborty, Gurindar S. Sohi
Venue: Proceedings of the 15th international conference on Parallel architectures and compilation techniques (2006)

Multiprocessor operating systems (OSs) pose several unique and conflicting challenges to System Virtual Machines (System VMs). For example, most existing system VMs resort to gang scheduling a guest OS's virtual processors (VCPUs) to avoid OS synchronization overhead. However, gang scheduling is infeasible for some application domains, and is inflexible in other domains.In an overcommitted environment, an individual guest OS has more VCPUs than available physical processors (PCPUs), precluding the use of gang scheduling. In such an environment, we demonstrate a more than two-fold increase in runtime when transparently virtualizing a chip-multiprocessor's cores. To combat this problem, we propose a hardware technique to detect several cases when a VCPU is not performing useful work, and suggest preempting that VCPU to run a different, more productive VCPU. Our technique can dramatically reduce cycles wasted on OS synchronization, without requiring any semantic information from the software.We then present a case study, typical of server consolidation, to demonstrate the potential of more flexible scheduling policies enabled by our technique. We propose one such policy that logically partitions the CMP cores between guest VMs. This policy increases throughput by 10-25% for consolidated server workloads due to improved cache locality and core utilization, and substantially improves performance isolation in private caches.
Combating Spam, Spyware, and Other Desktop Intrusions: Legal Considerations in Operating Trusted Intermediary Technologies
Authors: Charles D. Curran
Venue: IEEE Security and Privacy (2006)

To prevent spam, spyware, and other intrusions, network operators and software providers deploy trusted intermediary technologies to protect their end users and networks. These technologies can be designed to anticipate legal challenges that may be raised by the companies and other actors whose behaviors they inhibit.
Fusion of Detection and Matching Based Approaches for Laser Based Multiple People Tracking
Authors: Jinshi Cui, Huijing Zhao, Ryosuke Shibasaki
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Most of visual tracking algorithms have been achieved by matching-based searching strategies or detection-based data association algorithms. In this paper, our objective is to analysis laser scan image sequences to track multiple people in a crowded environment. Due to the poor features provided by laser scan images, neither of the above two approaches can achieves good tracking. To address the problem, we propose a novel multiple-target tracking algorithm fusing both detection and matching based strategies. First, target to detected measurement data association is incorporated to the joint state proposal, to form a mixture proposal that combines information from the dynamic model and the detected measurements. And then, we utilize a MCMC sampling step to obtain a more efficient multi-target filter. Our approach has been applied to the real laser scan image data. Evaluations show that the proposed method is a robust and effective multi-target tracking algorithm.
UNPCC: A Novel Unsupervised Classification Scheme for Network Intrusion Detection
Authors: Zongxing Xie, Thiago Quirino, Mei-Ling Shyu, Shu-Ching Chen, LiWu Chang
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

The development of effective classification techniques, particularly unsupervised classification, is important for real-world applications since information about the training data before classification is relatively unknown. In this paper, a novel unsupervised classification algorithm is proposed to meet the increasing demand in the domain of network intrusion detection. Our proposed UNPCC (Unsupervised Principal Component Classifier) algorithm is a multi-class unsupervised classifier with absolutely no requirements for any a priori class related data information (e.g., the number of classes and the maximum number of instances belonging to each class), and an inherently natural supervised classification scheme, both which present high detection rates and several operational advantages (e.g., lower training time, lower classification time, lower processing power requirement, and lower memory requirement). Experiments have been conducted with the KDD Cup 99 data and network traffic data simulated from our private network testbed, and the promising results demonstrate that our UNPCC algorithm outperforms several well-known supervised and unsupervised classification algorithms.
Different Brain Strategies Underlie the Categorical Perception of Foreign and Native Phonemes
Authors: Yasuyo Minagawa-kawai, Koichi Mori, Yutaka Sato
Venue: Journal of Cognitive Neuroscience (2005)

The present study using near-infrared spectroscopy examined the neuronal correlates of Japanese long/short vowel contrast discrimination and its relationship with behavioral performance by comparing native Japanese (L1) subjects and Korean subjects learning Japanese as a second language (L2). Phoneme-specific responses were predominantly observed in the left auditory area only in the L1 subjects, although the behavioral scores of the L2 subjects indicated categorical perception (CP) that was indistinguishable from that of the L1 subjects. These inconsistent relationships were more evident in the correlation coefficients between the brain recording and behavior. However, slower reaction times and non-specific brain responses in the L2 listeners suggest differences in their cortical processes from those of the L1 subjects. These findings suggest that the CP of L2 phonemes as determined by behavioral scores alone does not always predict a language-specific neural processing as employed by the L1 listeners.
Event-Related Potential Correlates of Long-Term Memory for Briefly Presented Faces
Authors: Carrie A. Joyce, Marta Kutas
Venue: Journal of Cognitive Neuroscience (2005)

Electrophysiological studies have investigated the nature of face recognition in a variety of paradigms; some have contrasted famous and novel faces in explicit memory paradigms, others have repeated faces to examine implicit memory/priming. If the general finding that implicit memory can last for up to several months also holds for novel faces, a reliable measure of it could have practical application for eyewitness testimony, given that explicit measures of eyewitness memory have at times proven fallible. The current study aimed to determine whether indirect behavioral and electrophysiological measures might yield reliable estimates of face memory over longer intervals than have typically been obtained with priming manipulations. Participants were shown 192 faces and then tested for recognition at four test delays ranging from immediately up to 1 week later. Three event-related brain potential components (e.g., N250r, N400f, and LPC) varied with memory measures although only the N250r varied regardless of explicit recognition, that is, with both repetition and recognition.
Web Service Testing Method Based on Fault-coverage
Authors: Wen-Li Dong, Hang YU
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

The aim of web service verification is how well the web service conforms to the WSDL specification and it is the key of web service popular adoption at present. In web service testing, the adequacy of test is the essence to verify if the software satisfies WSDL specification with the increasing complexity and applications of web service. This paper presents a systematic approach for web service testing based on fault-coverage which is intended to be used for service testing automation. In this method, HPNs representing operations are produced from WSDL specification after parsing process. A graph transforming from the HPN representing a web service is used to generate the adapted UIO sequence, then test sequence based on the adapted UIO sequence is given to acquire high fault coverage. Constraints-based test data generation for service testing getting sufficient test data to kill mutant program is presented in this paper. Constrains are departed to two kinds: user-defined and policy based on the syntactic and semantic analysis for WSDL specification. At last, we applied a test script language based on XML to effectively describe the test sequence. The test sequence and constrains for test data are expressed by this language. The test scenario is built on this formal language. The prototype system based on above method automating the web service test is developed in our lab.
The hidden dangers of experimenting in distributed AI
Authors: Annika Smit, Masja Kempen, Niek Wijngaards, André Meyer
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Research on multi-agent systems often involves experiments, also in situations where humans interact with agents. Consequently, the field of experimental (human) sciences becomes more and more relevant. This paper clarifies how things can and often do go wrong in distributed AI experiments. We show the flaws in methodological design in existing papers (both with and without humans) and work out an example involving human test-subjects to introduce the fundamental issues of experimental design. Furthermore, we provide researchers with an approach to improve their experimental design. We wish to stimulate researchers to conduct better experiments -- which will benefit us all.
Time-delayed feedback control method and unstable controllers
Authors: K. Pyragas
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

Time delayed-feedback control is an efficient method for stabilizing unstable periodic orbits of chaotic systems. The method is based on applying feedback proportional to the deviation of the current state of the system from its state one period in the past so that the control signal vanishes when the stabilization of the desired orbit is attained. A brief review of experimental implementations, applications for theoretical models, most important modifications as well as recent advancements in the theory of the method is presented. An idea of using unstable degrees of freedom in a feedback loop to avoid a well known topological limitation of the method is described in details. This idea is extended for the problem of adaptive stabilization of unknown steady states of dynamical systems. 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
An Interacting Systems Model of Infant Habituation
Authors: Sylvain Sirois, Denis Mareschal
Venue: Journal of Cognitive Neuroscience (2004)

Habituation and related procedures are the primary behavioral tools used to assess perceptual and cognitive competence in early infancy. This article introduces a neurally constrained computational model of infant habituation. The model combines the two leading process theories of infant habituation into a single functional system that is grounded in functional brain circuitry. The HAB model (for Habituation, Autoassociation, and Brain) proposes that habituation behaviors emerge from the opponent, complementary processes of hippocampal selective inhibition and cortical long-term potentiation. Simulations of a seminal experiment by Fantz [Visual experience in infants: Decreased attention familiar patterns relative to novel ones. Science, 146, 668&ndash;670, 1964] are reported. The ability of the model to capture the fine detail of infant data (especially age-related changes in performance) underlines the useful contribution of neurocomputational models to our understanding of behavior in general, and of early cognition in particular.
Analysis of an Intelligent Agent Intrusion Response System
Authors: Zeng-quan Wang, Hui-qiang Wang, Rui-jie Zhang
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

Analysis of the properties and the quality of IDS, take a mathematical analysis of the alarm confidence level, the attack frequency, the risk assessment and the response cost of IDS. Analysis of the tactic of IRS . Based on these, Analysis of an Intelligent Agent intrusion response system that is able to make automated response and adjust security policies according to the environmental variation dynamically.
Knowledge Management in mArachna
Authors: Sabina Jeschke, Nicole Natho, Thomas Richter, Ruedi Seiler, Marc Wilke
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

Machine-readable semantic annotation of scientific knowledge is becoming increasingly important to manage and access the knowledge contained in an increasing number of scientific publications. At the same time, automated extraction of knowledge from natural language texts is a major technical challenge remaining largely unsolved. Scientific texts in general, and mathematical texts in particular, are characterized by the use of complex language constructs with the intent to transfer knowledge. To a large extent, mathematical texts possess a strict internal structuring and can be separated into text elements such as definitions, theorems etc. These text elements are principal carriers of mathematical information. In addition, these elements show a characteristic linguistic structuring well suited for natural language processing techniques. In this paper we present mArachna, a system for extracting mathematical relations from texts and integrating them into a knowledge base. In response to user queries, parts of the knowledge base are visualized using OWL. In particular, mArachna aims to provide an overview of single fields of mathematics, as well as showing intrafield relations between mathematical objects and concepts.
Avoidance of Feature Interactions at Run-Time
Authors: Daisuke Harada, Hiroaki Fujiwara, Tadashi Ohta
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

Many researches for detecting feature interactions of telephony services have been discussed all over the world. But, there is no guarantee that all detected feature interactions can be resolved. In fact, services must be provided with unresolved feature interactions still remained. Consequently, a method for avoiding feature interactions at run-time is required. However, as far as the authors know, any effective solutions for avoiding feature interactions at run-time have not yet been proposed. In this article, it is clarified that even for services between which feature interactions occur, in some terminal assignments, feature interactions do not occur. Based on this fact, a method for avoiding feature interactions is proposed, where service initiation is prevented only when a terminal assignment causes feature interactions.
The Proliferation and Consolidation of Word Processing Software: 1985-1995
Authors: Thomas J. (Tim) Bergin
Venue: IEEE Annals of the History of Computing (2006)

Following development of the early word processing software packages--Electric Pencil, EasyWriter, and WordStar--and the IBM PC's arrival, the race among vendors began in earnest to win market share. Of the more than 400 software packages available in the mid-1980s, only a scant few survived. This article tells the story of how word processing software evolved in response to market pressures, new hardware capabilities, user demand, and corporate decision making.
Metavisual Exploration and Analysis of DEVise Coordination in Improvise
Authors: Chris Weaver
Venue: Proceedings of the Fourth International Conference on Coordinated & Multiple Views in Exploratory Visualization (2006)

Conceptualizing the interactive structure of visualization tools is critical for successful exploration and analysis. As the prominence of multiple coordinated views in visualization increases, better understanding of coordination becomes more and more important for developing improved coordination models that lead to farther reaching applications of coordination. This paper describes how metavisual exploration and analysis of coordination structure and view layout in DEVise visualizations evolved from hand-drawn diagrams to custom-coded software to two Improvise visualizations. The coordination and visual abstraction models implemented in Improvise can be clearly traced back to earlier models implemented in DEVise.
Hypercube based Team Multicast Routing Protocol for Mobile Ad hoc Networks
Authors: R. Manoharan, P. Thambidurai
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

In this paper, a novel multicast routing protocol namely Hypercube based Team Multicast Routing Protocol (HTMRP) has been proposed to address the scalability in mobile ad hoc networks. In HTMRP team multicasting is proposed where the multicast group does not consist of individuals rather, member teams. This mechanism is common in ad hoc networks to accomplish collective tasks such as emergency recovery, battle field where team affinity model exist when the member teams has a common interest. In MANET the link failures due to mobility is a big concern and is addressed in HTMRP by incorporating a logical hypercube model. The HTMRP also has a mesh layer on top of the hypercube for effective fault tolerance. In addition to scalability, HTMRP also guarantee the new QoS requirements namely high availability and good load balancing by incorporating team, hypercube and mesh tiers. The HTMRP has been simulated and extensively analyzed for scalability, delivery ratio and control overhead. The results show that HTMRP provides better performance for the above evaluation parameters than the existing multicast routing protocol.
An Information Theoretic Approach to Detection of Minority Subsets in Database
Authors: Shin Ando, Einoshin Suzuki
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Detection of rare and exceptional occurrences in large-scale databases have become an important practice in the field of knowledge discovery and information retrieval. Many databases include large amount of noise or irrelevant data, whose distribution often overlaps with the subsets of exceptional data containing useful knowledge. This paper addresses the problem of finding a small subset of "minority" data whose distribution overlaps with, but are exceptional to or inconsistent with that of the majority of the database. In such a case, conventional distance-based or density-based approaches in Outlier Detection are ineffective due to their dependence on the structure of the majority or the prerequisite of critical parameters. We formalize the task as an estimation of a model of the minority subset which provides a simple description of the subset and yet maintains divergence from that of the majority. This estimation is formalized as a minimization problem using an information theoretic framework of Rate Distortion theory. We further introduce conditions of the majority to derive an objective function which factorizes the property of the minority and dependence to the structure of the majority. The proposed method shows improvements from conventional approaches in artificial data and a promising result in document retrieval problem.
Big government software simulation projects for those who actually have to do it
Authors: Ralph R. Nebiker
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Practical tips for getting the job done. Software simulation development experiences the same problems, if not more, as do other large software development projects. Automated software development is the future of software engineering for large projects because manually supported coding and testing can't do the job, but automated software development is a big change for the government, which is based on managing people through document review. Change management and working with staffs slow to accept change is the biggest problem. Becoming proficient at abstraction was our biggest technical challenge. It was two years before we were able to stand on our own technically, and after three years some support personnel still didn't understand our process. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Random Sampling for Continuous Streams with Arbitrary Updates
Authors: Yufei Tao, Xiang Lian, Dimitris Papadias, Marios Hadjieleftheriou
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

The existing random sampling methods have at least one of the following disadvantages: they 1) are applicable only to certain update patterns, 2) entail large space overhead, or 3) incur prohibitive maintenance cost. These drawbacks prevent their effective application in stream environments (where a relation is updated by a large volume of insertions and deletions that may arrive in any order), despite the considerable success of random sampling in conventional databases. Motivated by this, we develop several fully dynamic algorithms for obtaining random samples from individual relations, and from the join result of two tables. Our solutions can handle any update pattern with small space and computational overhead. We also present an in-depth analysis that provides valuable insight into the characteristics of alternative sampling strategies and leads to precision guarantees. Extensive experiments validate our theoretical findings and demonstrate the efficiency of our techniques in practice.
An RNG-based heuristic for curve reconstruction
Authors: Asish Mukhopadhyay, Augustus Das
Venue: Proceedings of the 3rd International Symposium on Voronoi Diagrams in Science and Engineering (2006)

In this paper we propose an RNG-based heuristic for curve reconstruction. Given a set of n sample points S, we first construct a Relative Neighbourhood Graph on S, which is shown to contain all edges joining adjacent points on the unknown curve for an \in -sample with \in \lt 1/5. Next, we use a heuristic to remove non-adjacent edges. It is extremely simple and works remarkably well for sample points drawn from a large variety of curves.