ppxscal/embedding_network huggingface dataset:
Deferred Imitation of Action Sequences in Developmental Amnesia
Authors: Anna-Lynne R. Adlam, Faraneh Vargha-khadem, Mortimer Mishkin, Michelle De Haan
Venue: Journal of Cognitive Neuroscience (2005)

The aims of this study were to investigate whether patients with developmental amnesia (DA) associated with bilateral hippocampal volume reduction show an impairment in incidental nonverbal recall of action sequences, and whether the severity of this memory impairment is influenced by the sequence structure (causal vs. arbitrary). Like adult-onset cases of amnesia (McDonough, Mandler, McKee, & Squire, 1995), patients with DA did not differ significantly from their age-, sex-, and IQ-matched controls in spontaneous production of the sequences prior to modeling but recalled fewer target actions and action pairs than the control group after a 24-hour delay, independent of sequence structure. Unlike the patients with adult-onset amnesia, however, the patients with DA showed some memory for both types of sequences after a 24-hour delay. This difference in severity of memory impairment might reflect differences in extent of pathology and/or age at injury.
The Application of RFID Technology in Production Control in the Discrete Manufacturing Industry
Authors: Fagui Liu, Zhaowei Miao
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

RFID (Radio Frequency Identification), a technology existing for years, has potential uses in a variety of applications. Though not without issues and challenges, RFID is a promising technology which analysts expect to become ubiquitous in the coming years, helping organizations solve problems in supply chain management, security, personal identification, and asset tracking. The purpose of this paper is to applying RFID technology in production control in a discrete manufacturing system, which needs control the production process in real time in order to improve the management level of production efficiency and quality. In particular, we build a RAMS (RFID Activity Monitor System), for sanitary ware manufacturing, which is connected to the existing ERP System by database so as to satisfy real time control requirement.
Positive time-frequency distributions via maximum entropy deconvolution of the evolutionary spectrum
Authors: J. W. Pitton, P. J. Loughlin, L. E. Atlas
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04 (1993)

The relationship between Priestley's definition of the evolutionary densities (TFDs) is explored, and a synthesis method is presented. As defined by Priestley, the ES is not a member of the Cohen-Posch class of TFDs. However, it is shown that by choosing a unit-energy normalization for the envelope function of Priestley's formulation, the energetic ES thus obtained is a member of the Cohen-Posch class of TFDs; this normalization differs from that chosen by Priestley. A method is then presented to obtain an estimate of the energetic ES. This method employs maximum entropy deconvolution of the spectrogram, which is itself a blurred version of the ES. Because the energetic ES is everywhere nonnegative and yields the correct marginal densities, it is a legitimate, joint time-frequency energy density of the signal, unlike the Wigner and other bilinear distributions that go negative.
A deployed multi-agent framework for distributed energy applications
Authors: Geoff James, Dave Cohen, Robert Dodier, Glenn Platt, Doug Palmer
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper, we describe the adaptation of an open-source multi-agent platform for distributed energy applications and the trial deployment of resource-controller agents. The platform provides real-time, two-way communication and decision making between distributed energy resources --- loads and generators --- in electricity distribution networks. Such a decentralized architecture improves grid reliability, allows consumers to play a more active role in their energy usage, benefits the network by alleviating the effects of peak wholesale prices and network constraints, and creates new business opportunities in a deregulated market. Agents have been deployed to control hardware at trial locations in Australia, providing a realistic test environment for the platform, and medium-scale trials are anticipated in the near future.
Semi-Fragile Watermarking for Image Authentication with High Tampering Localization Capability
Authors: Huajian Liu, Martin Steinebach
Venue: Proceedings of the Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (2006)

In this paper we propose a novel watermarking scheme for image authentication. A high localization of tampering detection is achieved by applying a random permutation process where every embedded watermark bit verifies random image positions instead of a local image block. Thereby the resolution of tampering detection is significantly improved in comparison to existing solutions while keeping the payload low. Furthermore, the proposed scheme doesn't embed the watermark locally but distributes it into the suitable embedding wavelet coefficients, avoiding embedding in smooth regions. Therefore, the scheme is intrinsically secure to block-based local attacks and retains high fidelity of the watermarked image. Scalable sensitivity of tampering detection is enabled in the authentication process. Analysis and experimental results demonstrate the performance and effectiveness of the scheme for image authentication.
Digital signal processing aids cholesterol plaque detection
Authors: M. Savic, M. Chugani, K. Peabody, A. Husain, Ming-Hong Tang, Z. Macek
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

We describe four new methods for detection of cholesterol plaque deposits inside arteries, using digital signal processing. These methods have been tested on a number of patients. The results obtained are presented and discussed. An ultrasonic beam is directed towards the examined artery. Signal features obtained from the Doppler signal reflected from the bloodstream contain information about the character of turbulences caused by cholesterol deposits inside the artery. These features can thus provide information about the size, shape, and position of stenosis. Features in both the time and frequency domains were utilized, such as the LPC cepstrum, the exponential time-frequency distribution, the energy waveform and the wavelet transform.
Video transcoding in a grid network with user controlled lightpaths
Authors: Eduard Grasa, Sergi Figuerola, Joaquim Recio, Albert López, Marc de Palol, Lluis Ribes, Vicente Díaz, Ramon Sangüesa, Gabriel Junyent, Michel Savoie
Venue: Future Generation Computer Systems (2006)

GridON is an application that converts high-resolution broadcast video into MPEG-2 format, hereby reducing the file size and resolution. The application uses the user controlled lightpaths (UCLP) software to create on-demand, end-to-end, high-bandwidth dedicated connections to access remote computers. The converted MPEG-2 files can be distributed much faster and further than the source files to these dispersed computers, for reassembly into the higher resolution format. This paper describes the demonstration that took place last September at the iGrid 2005 conference held in San Diego. As a proof of concept, we successfully demonstrated that a video transfer in a Grid network environment can be integrated with a user-controlled lightpath provisioning system.
Opportunistic Pervasive Computing with Domain-Oriented Virtual Machines
Authors: J. Domaszewicz, M. Roj, A. Pruszkowski
Venue: Proceedings of the 9th EUROMICRO Conference on Digital System Design (2006)

The paper targets heterogeneous sensor-actuator networks, in which nodes differ as to resources (sensors and actuators) they are equipped with. Each node contributes its specific sensors and actuators to be used by applications. The key assumption of "opportunistic pervasive computing" is that the actual mix of nodes (and that of available resources) is not known in advance to the programmer. An opportunistic pervasive computing application is supposed to take the best advantage of whatever sensors and actuators happen to be available in the network. The paper presents a technique that can be used in middleware layers supporting such applications. The technique uses virtual machines to orderly expose sensor and actuator resources of a node to the programmer. The virtual machines are domain-oriented, node specific, and able to work with the resources at multiple levels of abstraction. They can be implemented on severely constrained nodes (e.g., of the TinyOS class).
Putting the Tools to Work: How to Succeed with Source Code Analysis
Authors: Pravir Chandra, Brian Chess, John Steven
Venue: IEEE Security and Privacy (2006)

Code analysis tools can play an essential role in creating secure software. They can help catchcommon coding mistakes such as buffer overflow, cross-site scripting, SQL injection, and a variety ofrace conditions. With a certain amount of customization, they can also provide for deeper, application-specific inspection as well as a general audit against custom coding standards.
Order Information in Working Memory: fMRI Evidence for Parietal and Prefrontal Mechanisms
Authors: Christy Marshuetz, Edward E. Smith, John Jonides, Joseph Degutis, Thomas L. Chenevert
Venue: Journal of Cognitive Neuroscience (2000)

Working memory is thought to include a mechanism that allows for the coding of order information. One question of interest is how order information is coded, and how that code is neurally implemented. Here we report both behavioral and fMRI findings from an experiment involved comparing two tasks, an item-memory task and an order-memory task. In each case, five letters were presented for storage, followed after a brief interval by a set of probe letters. In the case of the item-memory task, the two letters were identical, and the subject responded to the question, "Was this letter one of the items you saw?". In the case of the order-memory task, the letters were different, and subjects responded to the question, "Are these two letters in the order in which you saw them?". Behaviorally, items that were further apart in the sequence that elicited faster reaction times and higher accuracy in the Order task. Areas that were significantly more activated in the Order condition included the parietal and prefrontal cortex. Parietal activations overlapped those involved in number processing, leading to the suggestion that the underlying representation of order and numbers may share a common process, coding for magnitude.
A Dynamic Recognition of Human Actions and Related Objects
Authors: Masahiro Saitou, Atsuhiro Kojima, Tadahiro Kitahashi, Kunio Fukunaga
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In the field of image understanding, it is becoming popular to recognize human actions and objects in a scene to improve human-computer interaction. Recently, various methods for scene recognition have been proposed, and most of them focus on recognizing human actions and objects separately. We consider, however, it is important to recognize them complementarily, because human actions are closely related with objects. The relationship between actions and objects are represented by hierarchical models. First, movement of human head and hands are tracked by stereo vision. Features of actions such as position and direction of the head and hands are extracted and input to Dynamic Bayesian Networks to classify actions roughly. Then the actions and related objects are refined by using conceptual models of human actions and objects. Finally, detailed actions and objects are recognized by referring each models cooperatively.
Colored Petri Net Based Modeling of Airport Control Processes
Authors: Bernd Werther
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

The paper shows a formal approach for the description and modeling of work processes based on a cognitive work analysis. It is shown how the results of a cognitive work analysis on a medium size airport are transferred into a formal executable human machine model for simulating the controllers work processes to control the airport processes. The formal model serves for an evaluation of different variants of work organization, a design of a new working position and monitoring of psychological parameters. Critical system states and inconsistencies in the human machine system are identified through comparison of the knowledge state of the controllers with process states of the airport system. The first steps of model verification and validation are introduced in this paper.
A LCMS Rendering Intelligent Tutoring Modules for the Provision of Study Skills Training
Authors: C. Bermingham, A. E. Mahdi
Venue: Proceedings of the 15th International Conference on Computing (2006)

It is recognized that students in higher education need to acquire and develop effective and transferable skills in order to be successful in their study and after graduation. In this paper a new custom built LCMS, called the 'Skills SuperStore', which renders intelligent tutoring modules for the provision of study and transferable skills training, is presented and its performance evaluated. The proposed system has two principal units, administrator unit and student user unit. The administrator unit enables administrators with no knowledge of web application design and development to create and modify highly dynamic and engaging multimedia modules to be offered by the system. The student user unit delivers highly interactive and customized modules for the provision of skills training to students in higher education. The system's features, functionality and architecture were defined based on the findings of a viability study conducted at our institution. The system was developed using an iterative software prototyping.
LTL Model Checking via Search Space Partition
Authors: Fei Pu, Wenhui Zhang
Venue: Proceedings of the Sixth International Conference on Quality Software (2006)

The applicability of model checking is often limited by the size of the industrial system. This is known as state space explosion problem. Compositional verification has been particularly successful in this regard. This paper presents an approach based on a refinement of search space partition for reducing the complexity in verification of models with non-deterministic choices and open environment. The refinement depends on the representation of each portion of search space. Especially, search space can be refined stepwise to get better reduction. As reported in the case studies, search space partition improves the efficiency of verification with respect to the requirement of memory and obtains significant advantage over the use of the original one.
A noise-resistant algorithm for grid finding in microarray image analysis
Authors: Eugene Novikov, Emmanuel Barillot
Venue: Machine Vision and Applications (2006)

We present an algorithm for automatic spot localization for microarray images with rectangular spot and block packing. As an input, the algorithm requires only the common array design parameters: number of block rows and columns and number of spot rows and columns within each block. It proved to be robust with respect to different types of contamination and can tolerate a high percentage of the missing spots. The validity of the developed algorithm has been tested and confirmed using a large set of images of various designs from different microarray platforms. Comparison with academic and commercial packages has shown that for uncontaminated images our algorithm performs similarly, whereas for certain problematic images it outperforms the other packages.
A new look at signal-adapted QMF bank design
Authors: P. Moulin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

The design of a quadrature-mirror filter (QMF) bank (H,G) adapted to the input signal statistics is considered. The adaptation criterion is the maximization of the coding gain and has so far been viewed as a difficult nonlinear constrained optimization problem. It is shown that in fact the coding gain depends only upon the product filter P(z)=H(z)H(z/sup -1/). The optimization problem formulated in terms of the coefficients of P(z) gives rise to a linear semi-infinite program (SIP). A simple SIP algorithm using a discretization method is presented. The filter H(z) is obtained by deflation and spectral factorization of P(z). 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
A set theory for rough sets: toward a formal calculus of vague statements
Authors: Lech Polkowski
Venue: Fundamenta Informaticae (2006)

Rough set theory is a paradigm for approximate reasoning based on a formal mathematical basis, viz., it assumes that concepts are divided into exact and non-exact (rough) ones by means of a topological structure induced by a representation of knowledge as a classification. A classification in its most simple form is an equivalence relation on a universe of objects; the classification induces a partition topology and concepts (subsets of the universe) that are clopen are exact whereas other concepts are rough. In consequence, rough sets are represented as pairs of exact sets of the form (interior, closure).In the paper, we propose a set theory RZF that represents formally exact and rough sets as satisfying or not a certain dichotomy based on a new form of membership in a set; this membership acquires a mereological character as it is based on containment. As a result, we propose a new form of set theory suitable as a set theory for rough sets.Logical models for reasoning in the framework of rough set theory were proposed and studied by many researchers, among them Orłowska, Orłowska and Pawlak, Rasiowa and Skowron, Vakarelov. We exploit here models of RZF as interpretation domains for rough mereological logics: intensional logics whose truth value assignment is based on rough inclusions - basic predicates of rough mereology, a paradigm for approximate reasoning introduced by Polkowski and Skowron.An application for those logics is proposed in semantic interpretation of vague statements forming the domain of Calculus of Perceptions proposed by Zadeh.
Suspicious Financial Transaction Detection Based on Empirical Mode Decomposition Method
Authors: Tianqing Zhu
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

Traditional financial surveillance system usually discriminates suspicious transaction by comparing every transaction against its corresponding account history. This process always results in high false positive rate because it is regardless of the existence of economic cycle and business fluctuation. We conceived a new analyzingprototype by comparing an account time series transaction data against its peer group. It has deeply considered the injuence of normal jluctuation widely existing in real life and could eflciently reduce the number of false positives with a better understanding of customer 5. behavior pattern. A new method Empirical Mode Decomposition (EMD) developed initially for natural and engineering sciences has now been applied to financial time series data. This method has shown its superiorities in analyzing nonlinear and nonstationary stochastic engineering time series over traditional Discrete Fourier Decomposrtlon (DFD) and wavelet decomposition methods. Firstly the complex financial time series is decomposed into some local detail parts and one global tendency part which represent different time scales like daily, monthly, seasonal or annuat. Then a linear segment approximation method based on hierarchical piecewise linear representation (LPR) is used to fulfill the quick matching of the major tendency parts between two time series. The results from experiments on real life bank data lfoveign exchange transaction data sets) exhibit that the EMD can become a vital technique for the analysis offinancial suspicious transaction detection.
ns-3 project goals
Authors: Thomas R. Henderson, Sumit Roy, Sally Floyd, George F. Riley
Venue: Proceeding from the 2006 workshop on ns-2: the IP network simulator (2006)

This paper reports on the project plan to develop a new major version of the popular ns-2 networking simulator. The authors have organized an NSF-funded, four-year community infrastructure project to develop the next version of ns. The project will also be oriented towards community development and open source software practices to encourage participation from the broader research and educational community. The purpose of this paper is to expand on the goals and initial design concepts for this new software development effort.
On Recovering the Duffing System Based on a Modified Gradient Algorithm
Authors: Carlos Aguilar-Ibanez, Jorge Sanchez H., Ruben Garrido Moctezuma
Venue: Proceedings of the 15th International Conference on Computing (2006)

The paper presents a strategy for recovering the unknown parameters of the Duffing oscillator using only a measurable output signal. The suggested approach employs the construction of an integral parametrization of an auxiliary output, which is calculated by measuring the difference between the output and its respective time delayed version. First, we estimate the auxiliary output followed by the application of a modified gradient algorithm, then we adjust the gains of the proposed linear estimator in order to obtain convergence of the estimation error to zero. Convergence of the proposed scheme is shown using Lyapunov stability.
Evolutionary product unit based neural networks for regression
Authors: Alfonso Martínez-Estudillo, Francisco Martínez-Estudillo, César Hervás-Martínez, Nicolás García-Pedrajas
Venue: Neural Networks (2006)

This paper presents a new method for regression based on the evolution of a type of feed-forward neural networks whose basis function units are products of the inputs raised to real number power. These nodes are usually called product units. The main advantage of product units is their capacity for implementing higher order functions. Nevertheless, the training of product unit based networks poses several problems, since local learning algorithms are not suitable for these networks due to the existence of many local minima on the error surface. Moreover, it is unclear how to establish the structure of the network since, hitherto, all learning methods described in the literature deal only with parameter adjustment. In this paper, we propose a model of evolution of product unit based networks to overcome these difficulties. The proposed model evolves both the weights and the structure of these networks by means of an evolutionary programming algorithm. The performance of the model is evaluated in five widely used benchmark functions and a hard real-world problem of microbial growth modeling. Our evolutionary model is compared to a multistart technique combined with a Levenberg-Marquardt algorithm and shows better overall performance in the benchmark functions as well as the real-world problem.