ppxscal/embedding_network huggingface dataset:
Entrainment and musicality in the human system interface
Authors: Satinder P. Gill
Venue: AI Society (2007)

What constitutes our human capacity to engage and be in the same frame of mind as another human? How do we come to share a sense of what &#x2018;looks good&#x2019; and what &#x2018;makes sense&#x2019;? How do we handle differences and come to coexist with them? How do we come to feel that we understand what someone else is experiencing? How are we able to walk in silence with someone familiar and be sharing a peaceful space? All of these aspects are part of human &#x2018;interaction&#x2019;. In designing interactive technologies designers have endeavoured to explicate, analyse and simulate, our capacity for social adaptation. Their motivations are mixed and include the desires to improve efficiency, improve consumption, to connect people, to make it easier for people to work together, to improve education and learning. In these endeavours to explicate, analyse and simulate, there is a fundamental human capacity that is beyond technology and that facilitates these aspects of being, feeling and thinking with others. That capacity, we suggest, is human entrainment. This is our ability to coordinate the timing of our behaviours and rhythmically synchronise our attentional resources. Expressed within the movements of our bodies and voices, it has a quality that is akin to music. In this paper, disparate domains of research such as pragmatics, social psychology, behaviourism, cognitive science, computational linguistics, gesture, are brought together, and considered in light of the developments in interactive technology, in order to shape a conceptual framework for understanding entrainment in everyday human interaction.
Applying the Repgrid Technique to Resolve Cognitive Conflicts Among Experts During Knowledge Capture
Authors: Ananth Chiravuri, Derek Nazareth, K. Ramamurthy
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

There is an urgent need to understand and resolve conflict that may occur among multiple experts during the knowledge acquisition process so that it remains less of a "bottleneck". Our study addresses this need by examining the effectiveness of the Repertory Grid technique (Repgrid) in resolving cognitive conflicts among multiple experts in virtual teams during the process of knowledge capture. While the main study is ongoing, we present preliminary results from the pilot study conducted using real world experts. The results indicate that Repgrid technique is an effective technique in achieving consensus.
Clock tree analysis and synthesis considering process parameters and variability
Authors: Richard B. Brown, Dennis M. Sylvester
Venue:  (2006)

Clock distribution is vital to all synchronous integrated circuits; a poor clock distribution network can result in limited speed, high power consumption, and non-functional circuits. As process dimensions continue to scale, clock distribution faces ever increasing numbers of clock sinks and increased uncertainty in physical and electrical parameters that can significantly limit the yield of manufactured chips. This thesis examines clock tree analysis and synthesis in the presence of process parameters and variation by introducing concepts in statistical analysis, clock tree routing, and clock tree buffer/wire tuning. The efficient statistical analysis techniques developed enable optimization to route and tune variation-aware clock trees. A discretized algorithm for robust clock routing is presented that considers nominally unequal metal layers in addition to metal variations. Then, after the routes are buffered for slew reliability, the buffers and wires are tuned to minimize skew and increase robustness with optional power constraints using heuristics in both the deterministic and statistical timing domain. A novel sensitivity-matching algorithm is presented that allows clock tree skews to be correlated with data-path sensitivies to ameliorate sensitivity to variation. The result from the contributions in this thesis is improved robustness of clock trees in the presence of process variation. Our methods of routing, deterministic tuning, and statistical tuning showed improvements of 32.4%, 24.1%, and 16.3%, respectively, in terms of expected clock skew over traditional algorithms.
Promoting extension and reuse in a spoken dialog manager: An evaluation of the queen's communicator
Authors: Philip Hanna, Ian O'neill, Craig Wootton, Michael Mctear
Venue: ACM Transactions on Speech and Language Processing (TSLP) (2007)

This article describes how an object-oriented approach can be applied to the architectural design of a spoken language dialog system with the aim of facilitating the modification, extension, and reuse of discourse-related expertise. The architecture of the developed system is described and a functionally similar VoiceXML system is used to provide a comparative baseline across a range of modification and reuse scenarios. It is shown that the use of an object-oriented dialog manager can provide a capable means of reusing existing discourse expertise in a manner that limits the degree of structural decay associated with system change.
Banach-Mazur Distances and Projections on Random Subgaussian Polytopes
Authors: Rafal Latala, Piotr Mankiewicz, Krzysztof Oleszkiewicz, Nicole Tomczak-Jaegermann
Venue: Discrete Computational Geometry (2007)

We consider polytopes in ${\Bbb R}^n$ that are generated by N vectors in ${\Bbb R}^n$ whose coordinates are independent subgaussian random variables. (A particular case of such polytopes are symmetric random $\pm 1$ polytopes generated by N independent vertices of the unit cube.) We show that for a random pair of such polytopes the Banach-Mazur distance between them is essentially of a maximal order n. This result is an analogue of the well-known Gluskin's result for spherical vectors. We also study the norms of projections on such polytopes and prove an analogue of Gluskin's and Szarek's results on basis constants. The proofs are based on a version of "small ball" estimates for linear images of random subgaussian vectors.
Effect of Flat Fading in 802.11 MAC for Cross Layer Evaluation Using Channel Emulator
Authors: Adriano Almeida Goes, Omar Carvalho Branquinho, Norma Reggiani, Douglas Zambianco
Venue: Proceedings of the Second International Conference on Systems (2007)

WLAN 802.11 operating in 2,4 GHz are being intensely implanted mainly in public environments. In these environments mobility is always a present characteristic. The objective of this work is to analyze the behavior of 802.11 MAC with flat fading. To reach this objective an emulation system was developed to create the flat fading channel phenomenon. With a WLAN and the emulator was possible to show the cross layer effect, evaluating the WLAN performance analyzes in mobility conditions. The experiments evaluated: rate of transmission in each modulation level, data rate in the transport layer, network efficiency, jitter and throughput. The network information was obtained through SNMP. The results show that the 802.11 MAC had problems to support services that need high performance, as VoIP and Streaming. Therefore when the receiver is in movement the degradation does not allow the quality required by these types of services.
Testing Security Properties of Protocol Implementations - a Machine Learning Based Approach
Authors: Guoqiang Shu, David Lee
Venue: Proceedings of the 27th International Conference on Distributed Computing Systems (2007)

Security and reliability of network protocol implementations are essential for communication services. Most of the approaches for verifying security and reliability, such as formal validation and black-box testing, are limited to checking the specification or conformance of implementation. However, in practice, a protocol implementation may contain engineering details, which are not included in the system specification but may result in security flaws. We propose a new learning-based approach to systematically and automatically test protocol implementation security properties. Protocols are specified using Symbolic Parameterized Extended Finite State Machine (SP-EFSM) model, and an important security property - message confidentiality under the general Dolev-Yao attacker model - is investigated. The new testing approach applies black-box checking theory and a supervised learning algorithm to explore the structure of an implementation under test while simulating the teacher with a conformance test generation scheme. We present the testing procedure, analyze its complexity, and report experimental results.
Towards a Decentralized Algorithm for Mapping Network and Computational Resources for Distributed Data-Flow Computations
Authors: Shah Asaduzzaman, Muthucumaru Maheswaran
Venue: Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications (2007)

Several high-throughput distributed data-processing applications require multi-hop processing of streams of data. These applications include continual processing on data streams originating from a network of sensors, composing a multimedia stream through embedding several component streams originating from different locations, etc. These data-flow computing applications require multiple processing nodes interconnected according to the data-flow topology of the application, for on-stream processing of the data. Since the applications usually sustain for a long period, it is important to optimally map the component computations and communications on the nodes and links in the network, fulfilling the capacity constraints and optimizing some quality metric such as end-to-end latency. The mapping problem is unfortunately NP-complete and heuristics have been previously proposed to compute the approximate solution in a centralized way. However, because of the dynamicity of the network, it is practically impossible to aggregate the correct state of the whole network in a single node. In this paper, we present a distributed algorithm for optimal mapping of the components of the data flow applications. We propose several heuristics to minimize the message complexity of the algorithm while maintaining the quality of the solution.
A New Min-Cut Max-Flow Ratio for Multicommodity Flows
Authors: Oktay Gu&uml;nlu&uml;k
Venue: SIAM Journal on Discrete Mathematics (2007)

In this paper we present a new bound on the min-cut max-flow ratio for multicommodity flow problems with specified demands. For multicommodity flows, this is a generalization of the well-known relationship between the capacity of a minimum cut and the value of the maximum flow of a single commodity flow problem. For multicommodity flows, capacity of a cut is scaled by the demand that has to cross the cut to obtain the numerator of this ratio. In the denominator, the maximum concurrent flow value is used. Currently, the best known bound for this ratio is proportional to $\log(k)$, where $k$ is the number of origin-destination pairs with positive demand. Our new bound is proportional to $\log(k^*)$, where $k^*$ is the cardinality of the minimum cardinality vertex cover of the demand graph. To obtain this bound, we start with a so-called aggregated commodity formulation of the maximum concurrent flow problem with $k^*$ commodities. We also show a similar bound for the maximum multicommodity flow problem. The new bound is proportional to $\min\{\log(k^*), k^{**}\}$, where $k^{**}$ denotes the size of the of the demand graph.
2007 Special Issue: Online reservoir adaptation by intrinsic plasticity for backpropagation-decorrelation and echo state learning
Authors: Jochen J. Steil
Venue: Neural Networks (2007)

We propose to use a biologically motivated learning rule based on neural intrinsic plasticity to optimize reservoirs of analog neurons. This rule is based on an information maximization principle, it is local in time and space and thus computationally efficient. We show experimentally that it can drive the neurons' output activities to approximate exponential distributions. Thereby it implements sparse codes in the reservoir. Because of its incremental nature, the intrinsic plasticity learning is well suited for joint application with the online backpropagation-decorrelation or the least mean squares reservoir learning, whose performance can be strongly improved. We further show that classical echo state regression can also benefit from reservoirs, which are pre-trained on the given input signal with the implicit plasticity rule.
Erlang Reduced Load Model for Optical Burst Switched Grids
Authors: Marc De Leenheer, Chris Develder, Filip De Turck, Bart Dhoedt, Piet Demeester
Venue: Proceedings of the Third International Conference on Networking and Services (2007)

This paper presents an Erlang reduced load model to analyze Optical Burst Switched Grid networks. The model allows the evaluation of job blocking probabilities, in which blocking occurs in both the transport network and the resources where jobs are processed. Additionally, a novel routing strategy is introduced to improve the usage efficiency of the existing infrastructure. Simulation analysis is used to confirm the validity and accuracy of the model, and the effectiveness of the novel routing strategy is shown for Grids over OBS.
JANUS-II-translation of spontaneous conversational speech
Authors: A. Waibel, M. Finke, D. Gates, M. Gavalda, T. Kemp, A. Lavie, L. Levin, M. Maier, L. Mayfield, A. McNair, I. Rogina, K. Shima, T. Sloboda, M. Woszczyna, T. Zeppenfeld, P. Zhan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

JANUS-II is a research system to design and test components of speech-to-speech translation systems as well as a research prototype for such a system. We focus on two aspects of the system: (1) the new features of the speech recognition component JANUS-SR, and (2) the end-to-end performance of JANUS-II, including a comparison of two machine translation strategies used for JANUS-MT (PHOENIX and GLR*).
Enriching Group Profiles with Ontologies for Knowledge-Driven Colalborative Content Retrieval
Authors: Ivan Cantador, Pablo Castells, David Vallet
Venue: Proceedings of the 15th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (2006)

This paper proposes several strategies for the combination of ontology-based user profiles to generate a shared semantic profile for a group of users. The performance of the strategies is theoretically and empirically evaluated in an existing personalization framework from a knowledge-driven multimedia retrieval system. Early experiments are reported here, which show the benefits of using semantic user preferences representations and providing initial evidence as to which profiles combination strategies are most appropriate for collaborative content retrieval tasks.
Speech recognition over the Internet using Java
Authors: Zhemin Tu
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

A speech recognition system based on an Internet client-server model is presented in this paper. A Java applet records the voice at the client computer, sends the recorded speech file over the Internet, and the server computer recognizes the speech and displays the recognized text back to the user. Using this structure, an isolated digit recognition application was realized.
AquaLog: An ontology-driven question answering system for organizational semantic intranets
Authors: Vanessa Lopez, Victoria Uren, Enrico Motta, Michele Pasin
Venue: Web Semantics: Science, Services and Agents on the World Wide Web (2007)

The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input, and returns answers drawn from one or more knowledge bases (KBs). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.
Phone based email
Authors: Adil Attari
Venue: Proceedings of the 3rd annual conference on Atlanta Linux Showcase - Volume 3 (1999)

As electronic mail is becoming a standard way of communication, the ability to send e-mail even when you do not have physical access to a machine hooked to the Internet is of tremendous convenience. Using a touch-tone phone to dial-in to a machine that will carry on your email delivery seems to be a good solution for many situations. Today in the industry we find products that exploit this idea, yet requiring an additional piece of hardware to seize the text and dialing in to a remote e-mail server. Our approach is to use regular phone handsets to dial to your home machine-supposedly up, and your voice modem monitoring incoming phone calls, will allow you to send an e-mail, and forward each other calls to an answering machine.
Selecting keyword search terms in computer forensics examinations using domain analysis and modeling
Authors: David A. Dampier
Venue:  (2006)

The motivation for computer forensics research includes the increase in crimes that involve the use of computers, the increasing capacity of digital storage media, a shortage of trained computer forensics technicians, and a lack of computer forensics standard practices. The hypothesis of this dissertation is that domain modeling of the computer forensics case environment can serve as a methodology for selecting keyword search terms and planning forensics examinations. This methodology can increase the quality of forensics examinations without significantly increasing the combined effort of planning and executing keyword searches. The contributions of this dissertation include: (1) A computer forensics examination planning method that utilizes the analytical strengths and knowledge sharing abilities of domain modeling in artificial intelligence and software engineering, (2) A computer forensics examination planning method that provides investigators and analysts with a tool for deriving keyword search terms from a case domain model, and (3) The design and execution of experiments that illustrate the utility of the case domain modeling method. Three experiment trials were conducted to evaluate the effectiveness of case domain modeling, and each experiment trial used a distinct computer forensics case scenario: an identity theft case, a burglary and money laundering case, and a threatening email case. Analysis of the experiments supports the hypothesis that case domain modeling results in more evidence found during an examination with more effective keyword searching. Additionally, experimental data indicates that case domain modeling is most useful when the evidence disk has a relatively high occurrence of text-based documents and when vivid case background details are available. A pilot study and a case study were also performed to evaluate the utility of case domain modeling for typical law enforcement investigators. In these studies the subjects used case domain models in a computer forensics service solicitation activity. The results of these studies indicate that typical law enforcement officers have a moderate comprehension of the case domain modeling method and that they recognize a moderate amount of utility in the method. Case study subjects also indicated that the method would be more useful if supported by a semi-automated tool.
Making information flow explicit in HiStar
Authors: Nickolai Zeldovich, Silas Boyd-Wickizer, Eddie Kohler, David Mazières
Venue: Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7 (2006)

HiStar is a new operating system designed to minimize the amount of code that must be trusted. HiStar provides strict information flow control, which allows users to specify precise data security policies without unduly limiting the structure of applications. HiStar's security features make it possible to implement a Unix-like environment with acceptable performance almost entirely in an untrusted user-level library. The system has no notion of superuser and no fully trusted code other than the kernel. HiStar's features permit several novel applications, including an entirely untrusted login process, separation of data between virtual private networks, and privacypreserving, untrusted virus scanners.
Generalizing parametric timing analysis
Authors: Joel Coffman, Christopher Healy, Frank Mueller, David Whalley
Venue: Proceedings of the 2007 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems (2007)

In the design of real-time and embedded systems, it is important to establish a bound on the worst-case execution time (WCET) of programs to assure via schedulability analysis that deadlines are not missed. Static WCET analysis is performed by a timing analysis tool. This paper describes novel improvements to such a tool, allowing parametric timing analysis to be performed. Parametric timing analyzers receive an upper bound on the number of loop iterations in terms of an expression which is used to create a parametric formula. This parametric formula is later evaluated to determine the WCET based on input values only known at runtime. Effecting a transformation from a numeric to a parametric timing analyzer requires two innovations: 1) a summation solver capable of summation non-constant expressions and 2) a polynomial data structure which can replace integers as the basis for all calculations. Both additions permit other methods of analysis (e.g. caching, pipeline, constraint) to occur simultaneously. Combining these techniques allows our tool to statically bound the WCET for a larger class of benchmarks.
Pose-Dependent Level of Detail Model for Animated Grids
Authors: Tianding Chen, Xianli Xu
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

3D animation is now very popular in the movies and games. Since 3D animation in game is usually performed in real-time, complex models created by artist are often simplified to models of low polygon count. While many simplification methods have been proposed for static models, very few methods are available for the deformable grids. Current simplification methods for deformable grids are either computationally expensive or incapable of producing satisfactory results. In this paper, it proposes an efficient pose-dependent level of detail frame work for deformable grids. Its approach consists of two stages. The first stage preprocesses all costly computation steps and for each frame generates a simplified grid using a common vertex hierarchy. The second stage generates in-between grids between two consecutive key frames via connectivity blending and geometry interpolation. Results have showed that the proposed method is able to efficiently generate smooth transition between two pose-dependent grids, while requiring very little extra data storage.