ppxscal/embedding_network huggingface dataset:
Comparison of GALS and Synchronous Architectures with MPEG-4 Video Encoder on Multiprocessor System-on-Chip FPGA
Authors: Ari Kulmala, Timo D. Hamalainen, Marko Hannikainen
Venue: Proceedings of the 9th EUROMICRO Conference on Digital System Design (2006)

In large System-on-Chip (SoC) architectures, balancing the clock network is increasingly difficult. Globally Asynchronous Locally Synchronous (GALS) removes the need for global clock net, and also provides efficient means for managing the complexity and re-use in large architectures. However, quantitative comparisons of GALS against similar synchronous structures are rare for full SoC architectures. In this paper, we compare our SoC GALS architectures to a synchronous architecture with a fully functional MPEG-4 video encoder on FPGA. The results show that the area and performance overhead of GALS is only 1%. That is negligible compared to the benefits of the GALS architecture such as multiple clock frequencies for Intellectual Property (IP) blocks and dynamic frequency/voltage scaling, clock tree removal, and re-usability. Our architecture does not require modifications to the IP blocks already used with synchronous architectures, providing an ideal solution for rapid switch to GALS architecture.
Supporting Mobile Business Workflow with Commune
Authors: John Davis, Daby Sow, Daniela Bourges-Waldegg, Chang Jie Guo, Christian Hoertnagl, Markus Stolze, Brian White Eagle, Ying Yin
Venue: Proceedings of the Seventh IEEE Workshop on Mobile Computing Systems & Applications (2006)

Business workflow enables efficient specification and execution of a business process [1]. Through workflow, a business formally defines the algorithm of activities (steps) associated with a process and through a workflow management system, execution of this algorithm is automated to the degree possible. Recently workflow management systems have leveraged web services with BPEL serving as the premier means for specifying workflow as a composition of web services.
Enhancing Lifelong Competence Development and Management Systems with Social Network-based Concepts and Tools
Authors: Alicia M. Cheak, Albert A. Angehrn, Peter Sloep
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This paper addresses the challenge of enhancing the social dimension of lifelong Competence Development and Management Systems with social network-based concepts and tools. Our premise is that through a combination of social network visualization tools, simulations, stimulus agents and management policies, we may improve the self-organizing and knowledge sharing capabilities of communities of CDMS users. The ultimate objective is to increase system usage toward a sustainable level of knowledge exchange and creation.
Automatic Diagrams Analysis
Authors: M. A. Berbar
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

This paper presents fully automatic approach analysis for information extraction from digitized grey level images of scanned diagrams in the field of graphics recognition. The proposed algorithms were tested on Telecom Egypt diagrams and some randomly selected diagrams. The analysis involves three distinct stages: the location of starting pixels in the diag rams; followed by a model based line-following to separate the text and drawings; then applying a fitting and vectorization algorithm on lines and circles in the extracted drawings. The information is feed into database system for later use by technicians' staff. The first step is to separate between the graphic components and the text associated to them. The segmented texts are recognized by OCR system. The diagrams are segmented into graphics components as lines, curves, circles and filled regions. The ex tracted information from the recognized texts is matched with the recognized graphic components and are feed into a database system. The algorithm extracts 95% of drawing lines (cables ), and 100% of solid regions . The circle fitting and vectorization algor ithm is capable of estimating 95% of the extracted corners, semicircles, and circles in the drawings, even the circles that are in a complex touch with the text inside them.
Multiple window spectrogram and time-frequency distributions
Authors: G. Fraser, B. Boashash
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

We extend the spectrum estimation method of Thomson (1982, 1990) to non-stationary signals by formulating a multiple window spectrogram. The traditional spectrogram can be represented as a member of Cohen's class of time-frequency distributions (TFDs) where the smoothing kernel is the Wigner distribution of the signal temporal window. We show the unusual shape of the Cohen's class smoothing kernels corresponding to the Thomson method multiple windows. These are a class of smoothing kernels not hitherto used in time-frequency (t-f) analysis. Examples of the multiple window spectrogram applied to a noisy dual linear FM test signal and to actual underwater acoustic data demonstrate the merit of the method.
Increasing Software Engineering Efficiency Through Defect Tracking Integration
Authors: David Russell, Nilesh Patel
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

The creation of a collaboration system to facilitate updates to the defect tracking system, by extracting the defects status and resolution from the software engineers' code comments, will eliminate duplicated software engineer workload and inaccurate updates to the defect tracking system that result in lost or inaccurate metrics. This collaboration system will result in significantly improved productivity, traceability, and process compliance. Typically software quality assurance specialists will test the software and log defects within a defect tracking system. Software engineers will then correct the defect in the Integrated Development Environment (IDE), and update the status of the defect in the defect tracking system. Software engineers are required to enter the same information in the code comments, version control, and defect tracking system causing wasted software engineer time and lost opportunities to effectively capture historical metrics.
Normative KGP agents
Authors: Fariba Sadri, Kostas Stathis, Francesca Toni
Venue: Computational Mathematical Organization Theory (2006)

We extend the logical model of agency known as the KGP model, to support agents with normative concepts, based on the roles an agent plays and the obligations and prohibitions that result from playing these roles. The proposed framework illustrates how the resulting normative concepts, including the roles, can evolve dynamically during the lifetime of the agent. Furthermore, we illustrate how these concepts can be combined with the existing capabilities of KGP agents in order to plan for their goals, react to changes in the environment, and interact with other agents. Our approach gives an executable specification of normative concepts that can be used directly for prototyping applications.
A cubic polynomial system with seven limit cycles at infinity
Authors: Qi Zhang, Yirong Liu
Venue: Applied Mathematics and Computation (2006)

In this paper, we study bifurcation of limit cycles at infinity for a class of cubic polynomial system with no singular points at infinity, in which the problem for bifurcation of limit cycles from infinity be transferred into that from the origin. By computation of singular point values, the conditions of the origin (correspondingly, infinity) to be a center and the highest degree fine focus are derived. Consequently, we construct a cubic system which can bifurcate seven limit cycles from infinity when let normal parameters be suitable values. The positions of these limit cycles without constructing Poincaré. cycle fields can be pointed out exactly.
The Parametrization of All Stabilizing Multi-Period Repetitive Controllers for Time-Delay Systems with The Specified Input-Output Frequency Characteristics
Authors: Kou Yamada, Makoto Kowada
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In this paper, we examine the parametrization of all stabilizing multi-period repetitive controllers for singleinput/ single-output time-delay systems with the specified input-output frequency characteristics. The multi-period repetitive controller is proposed by Gotou et al. to improve the disturbance attenuation characteristics of the modified repetitive controllers. The parametrization of all multiperiod repetitive controller for non-minimum phase systems and that of all multi-period repetitive controllers for timedelay systems were solved by Yamada and Satoh. However, using the method by Yamada and Satoh, we cannot settle input-output characteristics easily. If the parametrization of all stabilizing multi-period repetitive controllers with the specified input-output characteristics is obtained, we can specify input-output characteristics easily. In this paper, we propose the parametrization of all stabilizing multi-period repetitive controllers with the specified input-output characteristics for time-delay systems.
Shape Representation and Distance Measure Based on Relational Graph
Authors: Jin Tang, Chunyan Zhang, Bin Luo
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

Nowadays, the efficient representation of a given shape plays a significant role in pattern recognition field. In this paper, we introduce a novel method to represent 2-D shape as a relation graph which using affine-invariant Fourier. This presentation method has invariance properties, such as scaling, shifting, rotation and starting point. Then edit distance is used to measure the distance between graphs. Embedding and recognition experiments are carried out to test the performance of affine-invariant Fourier based weighted graph(AFWG). Experimental results show that AFWG can preserve the shape feature well and can be applied to shape-related application.
On the computational content of the Lawson topology
Authors: Frédéric De Jaeger, Martín Escardó, Gabriele Santini
Venue: Theoretical Computer Science (2006)

An element of an effectively given domain is computable iff its basic Scott open neighbourhoods are recursively enumerable. We thus refer to computable elements as Scott computable and define an element to be Lawson computable if its basic Lawson open neighbourhoods are recursively enumerable. Since the Lawson topology is finer than the Scott topology, a stronger notion of computability is obtained. For example, in the powerset of the natural numbers with its standard effective presentation, an element is Scott computable iff it is a recursively enumerable set, and it is Lawson computable iff it is a recursive set. Among other examples, we consider the upper powerdomain of Euclidean space, for which we prove that Scott and Lawson computability coincide with two notions of computability for compact sets recently proposed by Brattka and Weihrauch in the framework of type-two recursion theory.
A New Steganalysis Method for Adaptive Spread Spectrum Steganography
Authors: Rongrong Ji, Hongxun Yao, Shaohui Liu, Liang Wang, Jianchao Sun
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

In this paper we focus on the detection of spread spectrum steganography, especially in the case that the scaling parameters are adaptive to image content. Our contribution is two folds. Firstly, we present a new steganalysis method for adaptive spread spectrum steganography: block-based scatter difference detection. Our algorithm first restores cover image by restoring filter. Then the embedding process is simulated in both test and cover images for certain times and the statistic in local DCT block is calculated as a criterion for classification. Secondly, we propose a region estimation algorithm to estimate the most likely stego regions. Our experiment result is promising by showing hits over 90% and false alarm lower than 10%. Its simplicity and extensibility indicate its further application in watermark detection.
Nonconservative stability problems for axially compressed rectangular plate
Authors: M. V. Belubekyan
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 4 (2003)

For investigation of nonconservative stability problems for beams, in general case, as it is well known, the dynamic approach is necessary. In this paper, stability problems for rectangular plates are considered. One of the edges of the plate is under compressive load, and displacements and turns of these edges are not constrained. On the other edges of plate several different boundary conditions are considered. The compressive load may have both 'follower' and 'non-follower' components.
Gaze tracking system using single camera and Purkinje image
Authors: Jinwoo Park, Yong-Moo Kwon, Kwanghoon Sohn
Venue: Proceedings of the 2005 international conference on Augmented tele-existence (2005)

A simple 2D gaze tracking algorithm using single camera and Purkinje image is proposed. This algorithm employs single camera with infrared filter to capture one's eye and two infrared point light sources to make reflection point, called Purkinje image, to estimate corresponding gaze point on the screen from user's eyes.
Object-based coding for long-term archive of surveillance video
Authors: A. Vetro, T. Haga, K. Sumi, H. Sun
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

This paper describes video coding and segmentation techniques that can be used to achieve significant increase in storage capacity. Specifically, we examine the possibility to use object- based coding for efficient long-term archiving of surveillance video. We consider surveillance systems with many camera sources in which we are required to store several months of video data for each source, thus storage capacity is a major concern. The paper considers several automatic segmentation algorithms. With each algorithm, we analyze the shape coding overhead and implication on overall storage requirements, as well as the effect each algorithm has on the reconstructed quality of frames. Additionally, this paper reviews techniques to dynamically control the temporal rate of objects in the scene and perform bit allocation. Experimental results show that up to 90% savings in storage can be achieved with the proposed method compared to frame-based video coding techniques. The cost for this savings is that the accuracy of the background is compromised; however, we feel that this is satisfactory for the application under consideration.
Diffusion Distance for Histogram Comparison
Authors: Haibin Ling, Kazunori Okada
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

In this paper we propose diffusion distance, a new dissimilarity measure between histogram-based descriptors. We define the difference between two histograms to be a temperature field. We then study the relationship between histogram similarity and a diffusion process, showing how diffusion handles deformation as well as quantization effects. As a result, the diffusion distance is derived as the sum of dissimilarities over scales. Being a cross-bin histogram distance, the diffusion distance is robust to deformation, lighting change and noise in histogram-based local descriptors. In addition, it enjoys linear computational complexity which significantly improves previously proposed cross-bin distances with quadratic complexity or higher. We tested the proposed approach on both shape recognition and interest point matching tasks using several multi-dimensional histogram-based descriptors including shape context, SIFT, and spin images. In all experiments, the diffusion distance performs excellently in both accuracy and efficiency in comparison with other state-of-the-art distance measures. In particular, it performs as accurately as the Earth Mover's Distance with much greater efficiency.
Partial & Holistic Face Recognition on FRGC-II data using Support Vector Machine
Authors: M. Savvides, R. Abiantun, J. Heo, S. Park, C. Xie, B. V. K. Vijayakumar
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

In this paper we investigate how to perform face recognition on the hardest experiment (Exp4) in Face Recognition Grand Challenge(FRGC) phase-II data which deals with subjects captured under uncontrolled conditions such as harsh overhead illumination, some pose variations and facial expressions in both indoor and outdoor environments. Other variations include the presence and absence of eye-glasses. The database consists of a generic dataset of 12,776 images for training a generic face subspace, a target set of 16,028 images and a query set of 8,014 images are given for matching. We propose to use our novel face recognition algorithm using Kernel Correlation Feature Analysis for dimensionality reduction (222 features) coupled with Support Vector Machine discriminative training in the Target KCFA feature set for providing a similarity distance measure of the probe to each target subject. We show that this algorithm configuration yields the best verification rate at 0.1% FAR (87.5%) compared to PCA+SVM, GSLDA+SVM, SVM+SVM, KDA+SVM. Thus we explore with our proposed algorithm which facial regions provide the best discrimination ability, we analyze performing partial face recognition using the eye-region, nose region and mouth region. We empirically find that the eye-region is the most discriminative feature of the faces in FRGC data and yields a verification rate closest to the holistic face recognition of 83.5% @ 0.1% FAR compared to 87.5%. We use Support Vector Machines for fusing these two to boost the performance to ~90@0.1 % FAR on the first large-scale face database such as the FRGC dataset.
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
Authors: Cristian Sminchisescu, Atul Kanaujia, Dimitris Metaxas
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion reconstruction. Learning progresses in alternative stages of self-training that optimize the probability of the image evidence: the recognition model is tunned using samples from the generative model and the generative model is optimized to produce inferences close to the ones predicted by the current recognition model. At equilibrium, the two models are consistent. During on-line inference, we scan the image at multiple locations and predict 3d human poses using the recognition model. But this implicitly includes one-shot generative consistency feedback. The framework provides a uniform treatment of human detection, 3d initialization and 3d recovery from transient failure. Our experimental results show that this procedure is promising for the automatic reconstruction of human motion in more natural scene settings with background clutter and occlusion.
Biclustering Protein Complex Interactions with a Biclique Finding Algorithm
Authors: Chris Ding, Ya Zhang, Tao Li, Stephen R. Holbrook
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Biclustering has many applications in text mining, web clickstream mining, and bioinformatics. When data entries are binary, the tightest biclusters become bicliques. We propose a flexible and highly efficient algorithm to compute bicliques. We first generalize the Motzkin-Straus formalism for computing the maximal clique from L_1 constraint to L_p constraint, which enables us to provide a generalized Motzkin-Straus formalism for computing maximal-edge bicliques. By adjusting parameters, the algorithm can favor biclusters with more rows less columns, or vice verse, thus increasing the flexibility of the targeted biclusters. We then propose an algorithmto solve the generalized Motzkin- Straus optimization problem. The algorithm is provably convergent and has a computational complexity of O(|E|) where |E| is the number of edges. Using this algorithm, we bicluster the yeast protein complex interaction network. We find that biclustering protein complexes at the protein level does not clearly reflect the functional linkage among protein complexes in many cases, while biclustering at protein domain level can reveal many underlying linkages. We show several new biologically significant results.
The Bottleneck Geodesic: Computing Pixel Affinity
Authors: Ido Omer, Michael Werman
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

A meaningful affinity measure between pixels is essential for many computer vision and image processing applications. We propose an algorithm that works in the features' histogram to compute image specific affinity measures. We use the observation that clusters in the feature space are typically smooth, and search for a path in the feature space between feature points that is both short and dense. Failing to find such a path indicates that the points are separated by a bottleneck in the histogram and therefore belong to different clusters. We call this new affinity measure the "Bottleneck Geodesic". Empirically we demonstrate the superior results achieved by using our affinities as opposed to those using the widely used Euclidean metric, traditional geodesics and the simple bottleneck.
Correlated Label Propagation with Application to Multi-label Learning
Authors: Feng Kang, Rong Jin, Rahul Sukthankar
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

Many computer vision applications, such as scene analysis and medical image interpretation, are ill-suited for traditional classification where each image can only be associated with a single class. This has stimulated recent work in multi-label learning where a given image can be tagged with multiple class labels. A serious problem with existing approaches is that they are unable to exploit correlations between class labels. This paper presents a novel framework for multi-label learning termed Correlated Label Propagation (CLP) that explicitly models interactions between labels in an efficient manner. As in standard label propagation, labels attached to training data points are propagated to test data points; however, unlike standard algorithms that treat each label independently, CLP simultaneously co-propagates multiple labels. Existing work eschews such an approach since naive algorithms for label co-propagation are intractable. We present an algorithm based on properties of submodular functions that efficiently finds an optimal solution. Our experiments demonstrate that CLP leads to significant gains in precision/recall against standard techniques on two real-world computer vision tasks involving several hundred labels.
Adaptive to Context in Ubiquitous Computing Environments
Authors: Jie Sun, ZhaoHui Wu
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

With the development of mobile devices and wireless communication technologies, users and devices will face an environment full of changes. It is indispensable for a system to adapt to the environment changes, which we call context-awareness. This paper introduces the adaptive mechanisms for embedded systems from the point of view of the data. The data in a context-aware system are in three different forms in different stage: the sensor data, the context, the situation. This paper introduces the context model which consists of three layers and the adaptive mechanisms in different layer to enable the system adaptive to contexts. Besides, we develop an example to show how the clustering and reasoning technology are used to recognize and derive the higher level context.