ppxscal/embedding_network huggingface dataset:
A reversible jump sampler for polynomial-phase signals
Authors: C. Theys
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

We use reversible jump Markov chain Monte Carlo (MCMC) methods to address the problem of order and parameters estimation of noisy polynomial-phase signals within a Bayesian framework. As posterior distributions of the parameters are not tractable, MCMC methods are used to simulate them. Efficient model jumping is achieved by proposing the model space moves from the conditional density of the polynomial coefficients, estimated with the "one variable at a time" Metropolis Hasting algorithm. This algorithm provides simultaneous order and parameters estimation from simulated marginal posterior distributions. Results on simulated data are given and discussed.
Critical Issues that Will Determine the Future of RFID
Authors: Aaron Wui Lun Wong, Dennis Viehland
Venue: Proceedings of the International Conference on the Management of Mobile Business (2007)

This study identifies the critical issues that will determine the future of radio frequency identification (RFID) and the likelihood of each issue being solved within the next two years. Results indicate that standardization is the most important issue and standardization is also the issue most likely to be solved within the next two years. System costs, business process reengineering, and integration also ranked high in importance. Privacy, lack of RFID-skilled professionals, and data warehousing were ranked low in importance for the future of RFID.
Neural network based person identification using EEG features
Authors: M. Poulos
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

A direct connection between the electroencephalogram (EEG) and the genetic information of an individual has been suspected and investigated by neurophysiologists and psychiatrists since 1960. However, most of this early as well as more recent research focuses on the classification of pathological EEG cases, aiming to construct tests for purposes of diagnosis. On the contrary, our work focuses on healthy individuals and aims to establish an one-to-one correspondence between the genetic information of the individual and certain features of his/her EEG, as an intermediate step towards the further goal of developing a test for person identification based on features extracted from the EEG. Potential applications include, among others, information encoding and decoding and access to secure information. At the present stage the proposed method uses spectral information extracted from the EEG non-parametrically via the FFT and employs a neural network (a learning vector quantizer-LVQ) to classify unknown EEGs as belonging to one of a finite number of individuals. Correct classification scores ranging from 80% to 100% in experiments conducted on real data, show evidence that the EEG indeed carries genetic information and that the proposed method can be used to construct person identification tests based on EEG features.
Research-Based-Decision-Making in Canadian Health Organizations: A Behavioural Approach
Authors: Jalila Jbilou, Nabil Amara, Réjean Landry
Venue: Journal of Medical Systems (2007)

Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment¿¿¿These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build networks, develop partnerships between professionals locally, regionally and nationally, and also act as change agents in the dissemination and adoption of knowledge and innovations in health services. However, the research focused on knowledge use as a support to decision-making, further research is needed to identify and evaluate effective incentives and strategies to implement so as to enhance RBDM adoption among health decision makers and more theoretical development are to complete in this perspective.
A Reverse-Engineering Approach to Understanding B Specifications with UML Diagrams
Authors: Akram Idani, Yves Ledru, Didier Bert
Venue: Proceedings of the 30th Annual IEEE/NASA Software Engineering Workshop (2006)

Formal methods are nowadays the most rigorous way to produce software. However, the existing formal notations are not easy to use and understand for most people. Our approach proposes to circumvent this shortcoming by producing complementary graphical views on the formal developments. This paper addresses the graphical representation of formal B specifications using UML diagrams. A reverse-engineering approach is proposed to generate several class diagrams showing the static aspects of the B developments. These diagrams can help understand the specification for stakeholders who are not familiar with the B method, such as customers or certification authorities. A concept formation technique based on weighted link matrices is proposed to improve automation.
High frequency distributed data stream event correlation to improve neonatal clinical management
Authors: Carolyn McGregor, Mike Stacey
Venue: Proceedings of the 2007 inaugural international conference on Distributed event-based systems (2007)

Approximately eighteen percent (18%) of babies born in New South Wales (NSW), Australia require special care or neonatal intensive care admission. Premature babies can be up to 17 weeks early and may only weigh 450gms; they can spend 3 or 4 months in intensive care and have dozens of specific diseases before discharge, many of these may have long term implications for the future health of the individual. In addition, fifteen percent of neonatal intensive care admissions are transferred after delivery from smaller regional or remote hospitals without intensive care facilities to larger Tertiary Referral or Children's Hospitals with Neonatal Intensive Care Units (NICUs). Similar conditions apply within Australia, New Zealand, Canada, USA and elsewhere where small non-tertiary units are spread throughout the country. This paper presents case study based applied research in progress supporting the development of a distributed event stream processing framework to enable high frequency distributed data stream event correlation to improve neonatal clinical management. This research extends the traditional notion of event-based approaches by extending the notion of an event to incorporate a composite event that exists over a period of time, as is required within the domain of health and medicine. This is achieved through a multi-agent event calculus based approach that supports temporal abstraction. A key contribution of this research is the ability to support automated medical condition onset detection.
Real-Time 3-D Ladar Imaging
Authors: Peter Cho, Hyrum Anderson, Robert Hatch, Prem Ramaswami
Venue: Proceedings of the HPCMP Users Group Conference (2006)

A prototype image processing system has recently been developed which generates, displays and analyzes three-dimensional ladar data in real-time. It is based upon a suite of novel algorithms that transform raw ladar data into cleaned 3-D images. These algorithms perform noise reduction, ground plane identification, detector response, deconvolution and illumination pattern renormalization. The system also discriminates static from dynamic objects in a scene. In order to achieve real-time throughput, we have parallelized these algorithms on a Linux cluster. We demonstrate that multiprocessor software plus Blade hardware result in a compact, real-time imagery generation adjunct to an operating ladar. Finally, we discuss interesting directions for future work like automatic recognition of moving people and real-time reconnaissance from mobile platforms. Such enhancements of our prototype imaging system can lead to multiple military and civilian applications of national importance.
A computationally-efficient two-step implementation of the GLRT detector
Authors: N. Pulsone
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

A new two-step implementation of the generalized likelihood ratio test (GLRT) is proposed. A disadvantage of the GLRT detector is that it is more computationally complex than the simple adaptive matched filter (AMF) detector. The two-step implementation of the GLRT significantly reduces the computational load with a negligible loss in detection performance.
Phase-based multidimensional volume registration
Authors: M. Hemmendorff
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

We present a method for accurate image registration and motion estimation in multidimensional volumes, such as 3D CT and MR images. The method is based on phase from quadrature filters, which makes it insensitive to variations in luminance and other disturbance in the images. The theory is not restricted to any particular kind of motion model or number of dimensions. Experimental results for affine motions in 3D show high accuracy.
Establishing Visual Correspondence from Multi-Resolution Graph Cuts for Stereo-Motion
Authors: Joshua Worby, W. James MacLean
Venue: Proceedings of the Fourth Canadian Conference on Computer and Robot Vision (2007)

This paper presents the design and implementation of a multi-resolution graph cuts (MRGC) for stereo-motion framework that produces dense disparity maps. Both stereo and motion are estimated simultaneously under the origi- nal graph cuts framework [7]. Our framework extends the problem from one to five dimensions, creating a large in- crease in complexity. Using three different multi-resolution graph cut algorithms, LDNR, EL and SAC, we reduce the number of pixelsmand the number of labels n that limit the á . â swap algorithm (with complexity O(mn2) required from the definition of our semi-metric smoothness function. This results in a reduction of computation time and the abil- ity to handle larger images and larger label sets. The choice of the three MRGC algorithms to use in computation deter- mines the appropriate level of accuracy and computation time desired.
Miniature animal computer interfaces: applied to studies of insect flight and primate motor pathways
Authors: Chris Diorio
Venue:  (2006)

The actions of even the most advanced robotic machines are primitive in comparison to mundane tasks performed by animals. Although, we can crudely emulate the mechanics of skeletal joints and muscles with the latest fabrication techniques and materials, we do not yet fully understand the control algorithms innate to biological neuromuscular systems. Stimulus-response experimentation, a traditional tool used by neurobiologists to understand the working principles of the biological systems, is conventionally done with unnaturally constrained or reduced animal preparations with artificial stimuli. Though such experiments have contributed to a wealth of information about animal brains, results obtained under restricted conditions do not reflect the full repertoire of neuromuscular activity that occurs during natural behaviors. For example, electrophysiological experiments to study flapping flight of insects use insects glued on sticks so that desktop instrumentation can record neuromuscular activity via implanted microwires. Similarly, studies of primate motor cortex function have conventionally relied on monkeys performing repetitive, over-trained tasks and confined within a restricted workspace. To enable experiments in freely behaving organisms in order to understand the neural correlates of intelligent animal behavior, I have developed a family of miniature implantable circuits ("neurochips"). The circuits include: (1) ultra-light data recorders and stimulators for free-flight experiments to reverse engineer flapping insect flight, and (2) autonomous brain-computer-interfaces for primates to understand the functioning of neuromuscular control. My neurobiologist colleagues and I have used the neurochips for a variety of experiments to study in-flight maneuvering in hawkmoths, cataloging brain-motor activity and inducing cortical plasticity in freely behaving macaques. This dissertation describes the neurochip designs and compiles several results from these experiments. The present neurochips have very few recording and stimulation channels, limiting our experimental paradigms. So, I propose future neurochip architectures to scale the number of channels, as well as an analog spike classifier module to discriminate multiple spikes from multiple neural signals.
Exploring the acceptance of mobile auctions in China
Authors: Shuo Wang, Stuart Barnes
Venue: Proceedings of the International Conference on the Management of Mobile Business (2007)

The growth of mobile phone usage and online auctions in China has been extremely rapid. Recently, these trends have started to converge, as online auctions players such as Eachnet (eBay China) try to diversify and gain competitive advantage via the creation of mobile auctions. Although relatively embryonic, the potential for this new business model is immense. With this in mind, we were interested to learn how likely m-auctions are to be accepted and used. The research question we attempt to answer is: "What factors are likely to influence attitudes and behavioural intention towards mobile auctions in China?" The methodology is based on the testing of a statistical model founded on the technology acceptance literature with a sample of more than 200 respondents. The findings are then discussed in light of the theoretical literature. The paper rounds off with a summary and conclusions, examining implications for future research and practice.
A new directional filter bank for image analysis and classification
Authors: Sang-Il Park
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

A new directional filter bank for image analysis and classification is proposed. This paper introduces an improved structure in order to visualize subband outputs of the directional filter banks, while retaining the attractive properties of the original directional filter banks such as 1-D separable filtering, perfect reconstruction, and maximal decimation. Using this structure, any arbitrary 2/sup n/ band directional filter bank can be implemented by cascading simple directional filter bank blocks, unlike the original structure that needs a parallel structure for visualizing subband outputs. Also, in order to have nondistorted phase information in the subbands for visualization, both FIR and IIR filter prototypes that can be implemented efficiently are provided for linear phase filtering. This paper shows the approach proposed here can be applied to image analysis and classification.
Remote Awareness of Complicated Pattern Group in Ubiquitous Collaborative Graphics Editing Systems
Authors: Bo Jiang, Guozheng Wang
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

The proliferation of computer devices and wireless networks allows users to access pattern information and collaborative edit graphics with others in ubiquitous environment. However, the limitation of display size and unreliable network of these embedded devices makes it hard for mobile users to browse grouped complicated pattern objects efficiently. We propose semantic group mapping that enable group node representation form on mobile devices and the corresponding operation sending scheme that can provide on demand detailed group information and maintain the consistency of pattern replicas on mobile site. The scheme is realized in our prototype system of collaborative graphics editing system that can work well in ubiquitous environment.
The Case for FEC-Based Reliable Multicast in Wireless Mesh Networks
Authors: Dimitrios Koutsonikolas, Y. Charlie Hu
Venue: Proceedings of the 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (2007)

Many important applications in wireless mesh networks require reliable multicast communication. Previously, Forward Error Correction (FEC) techniques have been proved successful for providing reliability in the Internet, as they avoid the control packet implosion and scalability problems of ARQ-based protocols. In this paper, we examine if FEC can be equally efficientin wireless mesh networks. We implement four reliable schemes initially proposed for wired networks on top of ODMRP, a popular unreliable multicast routing protocol for wireless networks. We compare the performance of the four schemes using extensive simulations. Our results show that the use of pure FEC can offer significantimprovements in terms of reliability, increasing PDR up to 100% in many cases, but it can be very inefficient regarding the number of redundant packets it transmits. Moreover, a carefully designed hybrid protocol, such as RMDP, can maintain the same high level of reliability while improving the efficiencyby up to 38% compared to a pure FEC scheme.
The Strength of Virtuality in Teams: Social Capital built on Weak Ties
Authors: Keith Dixon, Niki Panteli
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

Research into virtual teams has long focused on "glass half-empty" comparisons with "traditional" teams, exploring the ramifications of technologymediated interactions that lack the social context and cues of face-to-face encounters. With this paper we extend an emerging argument for a new perspective focusing instead on a more optimistic picture in which the glass is actually half-full and technology-mediated interactions play a positive role alongside face-to-face interactions in teams. To achieve this we employ social capital, and in particular "weak ties", as a sensitizing concept or lens through which to view the emerging perspective of "virtuality", defined in terms of "discontinuities" in teams. The thinking this develops is used to examine data gathered from a year-long case study of a UK government-funded "virtual centre of excellence". The findings highlight task and membership boundaries as unique additional discontinuities to be considered in the definition of virtuality.
Subword-based tagging for confidence-dependent Chinese word segmentation
Authors: Ruiqiang Zhang, Genichiro Kikui, Eiichiro Sumita
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

We proposed a subword-based tagging for Chinese word segmentation to improve the existing character-based tagging. The subword-based tagging was implemented using the maximum entropy (MaxEnt) and the conditional random fields (CRF) methods. We found that the proposed subword-based tagging outperformed the character-based tagging in all comparative experiments. In addition, we proposed a confidence measure approach to combine the results of a dictionary-based and a subword-tagging-based segmentation. This approach can produce an ideal tradeoff between the in-vocaulary rate and out-of-vocabulary rate. Our techniques were evaluated using the test data from Sighan Bakeoff 2005. We achieved higher F-scores than the best results in three of the four corpora: PKU(0.951), CITYU(0.950) and MSR(0.971).
Light context-sensitive points-to analysis for java
Authors: Ana Milanova
Venue: Proceedings of the 7th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering (2007)

We design a new context-sensitive points-to analysis for Java thattargets key object-oriented features such as inheritance and encapsulation, and improves precision over the Andersen-style context-insensitive analysis. At the same time, it has cubic worst-case complexity, thus giving precision improvement for free.
Building a notification infrastructure using Tcl, Zephyr, and Linda
Authors: W. Scott Meeks
Venue: Proceedings of the 5th conference on Annual Tcl/Tk Workshop 1997 - Volume 5 (1997)

This poster describes the design and implementation of a notification system that can be integrated with other Web tools and applications. A Tcl-based toolkit using the MIT Zephyr Notification System was built to allow applications to notify each other or a user of relevant changes in information. A blackboard service was built using the notification toolkit and a server for the Linda language. This service is used to selectively store notifications for later use by applications. The use and effectiveness of the toolkit and service were demonstrated in an application for conducting a distributed guided tour of individual Web pages, and by integrating notifications from our Mediator service into our HistoryGraph application.
Stability analysis of efficient solutions in multiobjective integer programming: A case study in load management
Authors: Maria João Alves, João Clímaco, Carlos Henggeler Antunes, Humberto Jorge, António G. Martins
Venue: Computers and Operations Research (2008)

This paper presents a multiobjective linear integer programming model for supporting the choice of remote load control strategies in electric distribution network management. The model takes into account the main concerns in load management, considering three objective functions: minimization of the peak demand as perceived by the distribution network dispatch center, maximization of the utility profit associated with the energy services delivered by the controlled loads and minimization of the discomfort caused to consumers. The problem was analyzed using an interactive reference point method for multiobjective integer (and mixed-integer) linear programming. This approach exploits the use of the branch-and-bound algorithm for solving the reference point scalarizing programs through which efficient solutions are computed. Post-optimality techniques enable a stability analysis of the efficient solutions by means of computing and displaying graphically sets of reference points that correspond to the same solution.