ppxscal/embedding_network huggingface dataset:
A Local-Global Graph Approach for Facial Expression Recognition
Authors: P. Kakumanu, N. Bourbakis
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

In this article, we present a Local Global Graph (LGG) method for recognizing facial expressions from static images irrespective of different illumination conditions, shadows and cluttered backgrounds. First, a neural color constancy based skin detection procedure to detect skin in complex real world images is presented. Second, the LGG method for detecting faces and facial expressions with a maximum confidence from skin segmented images is presented. The LGG approach presented here emulates the human visual perception for face and expression detection. In general, humans first extract the most important facial features such as eyes, nose, mouth, etc. and then inter-relate them for face and facial expression representations. The LG Graph embeds both the local information (the shape of facial feature is stored within the local graph at each node) and the global information (the topology of the face). Facial expression recognition from the detected face images is obtained by comparing the LG Expression Graphs with the existing the LG expression models present in the LGG database. Experimental results on the AR database and real-world images suggest the robustness of the proposed approach for facial expression recognition.
HiveFlex Video VSP1 Demonstration
Authors: Aleksandar Beric, Carlos Alba Pinto
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

This work presents a real-time demonstrator system for the VSP1 Tile. The complete 8-way SIMD VSP1 Tile is implemented on the demonstration platform based on the Xilinx Virtex2 XC2V8000 FPGA chip. The application running on a VSP1 Tile is spatial upscaling. This is a challenging application since it is based on a pixel-based algorithm using content adaptive filtering. The FPGA running on 25 MHz is capable of achieving 17.3 fps for input sequence (320*192) producing four times bigger output sequence (640*384).
Unconscious Detection of Implicit Expectancies
Authors: Michael Rose, Hilde Haider, Christian Büchel
Venue: Journal of Cognitive Neuroscience (2005)

The detection of unexpected events is a fundamental process of learning. Theories of cognitive control and previous imaging results indicate a prominent role of the prefrontal cortex in the evaluation of the congruency between expected and actual outcome. In most cases, this attributed function is based on results where the person is consciously aware of the discrepancy. In this functional magnetic imaging (fMRI) study, we examined violations of predicted outcomes that did not enter conscious awareness. Two groups were trained with nearly identical material and the effects of new stimuli were assessed after learning. For the first group, the material was arranged with a hidden regularity. In this incidental learning situation, volunteers acquired implicit knowledge about structural response regularities as was demonstrated by an increase in reaction time when introducing new stimuli that violated the learned relations. To differentiate the detection process of stimuli that deviate from learned expectations from more unspecific effects generated by novel, unfamiliar stimuli, the second group was trained with rearranged material without a hidden regularity. No behavioral effects were found for the introduction of new stimuli in the group without implicit learning. Comparing the two groups, specific fMRI effects concerning the violation of implicitly learned expectations were found in the ventral prefrontal cortex and in the medialtemporal lobe.In accord with theories of learning, the results show a direct influence of the detection of prediction errors on the neuronal activity in learning related structures even in the absence of conscious knowledge about the predictions or their violations.
The dynamics of the best individuals in co-evolution
Authors: Elena Popovici, Kenneth De Jong
Venue: Natural Computing: an international journal (2006)

There continues to be a growing interest in the use of co-evolutionary algorithms to solve difficult computational problems. However, their performance has varied widely from good to disappointing. The main reason for this is that co-evolutionary systems can display quite complex dynamics. Therefore, in order to efficiently use co-evolutionary algorithms for problem solving, one must have a good understanding of their dynamical behavior. To build such understanding, we have constructed a methodology for analyzing co-evolutionary dynamics based on trajectories of best-of-generation individuals. We applied this methodology to gain insights into how to tune certain algorithm parameters in order to improve performance.
Constrained least square design of FIR filters without specified transition bands
Authors: I. W. Selesnick, M. Lang, C. S. Burrus
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

We consider the design of digital filters and discuss the inclusion of explicitly specified transition bands in the frequency domain design of FIR filters. We put forth the notion that explicitly specified transition bands have been introduced in the filter design literature as an indirect and sometimes inadequate approach for dealing with discontinuities in the desired frequency response. We also present a rapidly converging, robust, simple algorithm for the design of optimal peak constrained least square lowpass FIR filters that does not require the use of transition bands. This versatile algorithm will design linear and minimum phase FIR filters and gives the best L/sub 2/ filter and a continuum of Chebyshev filters as special cases.
A novel approach to scalable CAC for real-time traffic in sink-tree networks with aggregate scheduling
Authors: Luciano Lenzini, Linda Martorini, Enzo Mingozzi, Giovanni Stea
Venue: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools (2006)

In this paper we investigate the problem of scalable admission control for real-time traffic in sink-tree networks employing per-aggregate resource management policies, like MPLS or DiffServ. Every traffic flow entering the network at an ingress node, and flowing towards a given egress node, specifies its leaky-bucket parameters and a required delay bound for traversing the network. We propose an algorithm that admits a new flow if a guarantee can be given that the required delay bound, besides those of other already established flows, are not exceeded. We identify properties of sink-tree networks based on which we considerably reduce the complexity of the proposed algorithm, and we show that the latter approaches the theoretical lower bound on the worst case complexity of any algorithm working under the same hypotheses. Finally, we show that the algorithm lends itself to a distributed implementation, thus allowing for better scalability.
Optimal strategy for graceful network upgrade
Authors: Ram Keralapura, Chen-Nee Chuah, Yueyue Fan
Venue: Proceedings of the 2006 SIGCOMM workshop on Internet network management (2006)

One of the critical aspects of network management that has not received much attention is network upgrade. This paper addresses the question of "how to add new nodes and links into an operational network in a graceful manner so that the perceived network performance from the perspective of existing customers does not deteriorate?". We propose a two-phase framework to find the optimal upgrade strategy: first, deciding what nodes should be added and how they should be connected to existing topology, and second, deciding the ideal sequence to add these new nodes and links. We formulate the first phase as a non-linear optimization problem and the second phase as a multistage dynamic programming problem. Through a numerical example, we show the feasibility of this framework and demonstrate the advantages of our multistage approach in determining an ideal upgrade sequence. The results also highlight the significance of incorporating network performance (for ex, service availability) into the two-phase framework to achieve minimal impact to existing customers.
A Real Time Speckle Noise Cleaning Filter for Ultrasound Images
Authors: B. Mazumdar, A. Mediratta, J. Bhattacharyya, S. Banerjee
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Ultrasound images are masked by multiplicative speckle noise caused by random interference between coherent backscattered waves. This paper presents an efficient algorithm for real-time speckle cleaning filter of ultrasound images and its VLSI implementation in FPGA. The algorithm presented here implements a regular, tunable filter with an optimized architecture having proper parallelism and pipelining to achieve high speed. The performance of the proposed filter is compared to that of the Aggressive Region Growing Filter (ARGF). The processed images obtained from the proposed filter are speckle removed and the edge details are also restored effectively. Also, the PSNR performance is better than the ARGF filter while Noise Variance is lower indicating a cleaner image as more speckle is reduced.
The development of Chez Scheme
Authors: R. Kent Dybvig
Venue: Proceedings of the eleventh ACM SIGPLAN international conference on Functional programming (2006)

Chez Scheme is now over 20 years old, the first version having been released in 1985. This paper takes a brief look back on the history of Chez Scheme's development to explore how and why it became the system it is today.
LAPIN-SPAM: An Improved Algorithm for Mining Sequential Pattern
Authors: Zhenglu Yang, Masaru Kitsuregawa
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Sequence pattern mining is an important research problem because it is the basis of many other applications. Yet how to efficiently implement the mining is difficult due to the inherent characteristic of the problem - the large size of the data set. In this paper, by combining SPAM, we propose a new algorithm called LAst Position INduction Sequential PAttern Mining (abbreviated as LAPIN-SPAM), which can efficiently get all the frequent sequential patterns from a large database. The main difference between our strategy and the previous works is that when judging whether a sequence is a pattern or not, they use S-Matrix by scanning projected database (PrefixSpan) or count the number by joining (SPADE) or ANDing with the candidate item (SPAM). In contrast, LAPIN-SPAM can easily implement this process based on the following fact - if an item's last position is smaller than the current prefix position, the item can not appear behind the current prefix in the same customer sequence. LAPIN-SPAM could largely reduce the search space during mining process and is considerable effectiveness in mining sequential pattern. Our experimental results show that LAPIN-SPAM outperforms SPAM up to three times on all kinds of dataset.
Graph Partitioning by Spectral Rounding: Applications in Image Segmentation and Clustering
Authors: David A. Tolliver, Gary L. Miller
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

We introduce a family of spectral partitioning methods. Edge separators of a graph are produced by iteratively reweighting the edges until the graph disconnects into the prescribed number of components. At each iteration a small number of eigenvectors with small eigenvalue are computed and used to determine the reweighting. In this way spectral rounding directly produces discrete solutions where as current spectral algorithms must map the continuous eigenvectors to discrete solutions by employing a heuristic geometric separator (e.g. k-means). We show that spectral rounding compares favorably to current spectral approximations on the Normalized Cut criterion (NCut). Results are given for natural image segmentation, medical image segmentation, and clustering. A practical version is shown to converge.
Fractionally spaced CMA equalizers under periodic and correlated inputs
Authors: J. P. LeBlanc, I. Fijalkow, B. Huber
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

CMA fractionally spaced equalizers (CMA-FSEs) have been shown, under certain conditions, to be globally asymptotically convergent to a setting which provides perfect equalization. Such a result relies heavily on the assumptions of a white source and no channel noise (as is the case in much of the literature's analysis of CMA). Herein, we relax the white source assumption and examine the effect of source correlation on CMA. Analytic results are meshed with examples showing CMA-FSE source correlation effects. Techniques for finding all stationary and saddle points on the CMA-FSE error surface are presented using recent developments in the algebraic-geometry community.
How to Cheat at IT Project Management
Authors: Nels Hoenig, Susan Snedaker
Venue:  (2005)

Project Management Made Fast and Easy for IT Professionals Unlike any other book you'll find, this IT project management book synthesizes project management fundamentals, IT processes and procedures, and business fundamentals. Learn how to align your IT projects to the company's strategic objectives. Also learn how to determine which project will solve the right problem at the right time while still delivering high-quality results. You'll become an expert in fine-tuning the work process to ensure projects are completed on time, under budget, and with the required functionality and features. If you've ever wondered how to get on the fast track to CIO...you might just be holding the answer in your hands. Align IT Projects with Corporate Strategy: Run your IT department more like a business and use IT projects to support or extend the corporate mission. Navigate Corporate Politics: Develop the skills you need to succeed in a political environment, even if you really dislike company politics. Effectively Manage Your IT Project Team: Master the complexities of managing teams of people with different work styles, languages, cultures, and generations. Define and Design Successful IT Projects: Learn the seven major steps of the project management process: define, organize, form the team, plan, manage, track, and close the project. Build High-Quality Projects from the Ground Up: Deliver higher quality project results using consistent, repeatable, easy-to-use steps. Create a Work Breakdown Structure (WBS) : Delineate the work to be accomplished and identify task owner, entry/exit criteria, and completion criteria. Mitigate "Scope Creep" in Your Projects: Continually analyze proposed changes to projects and avoid the ripple effect of making unnecessary changes or additions to the scope of your projects. Manage IT Project Risk, Change, and Variance: Incorporate new tools and techniques to manage the risks that change and variance inject into your IT project. Complete a Project Audit: Examine your project's goals, achievements, deliverables, and metrics against compliance with scope, time, cost, and quality requirements. REVISED TOC Chapter 1 What's Project Management Got To Do With IT? Chapter 2 What's Corporate Strategy Got To Do With IT? Chapter 3 Navigating Corporate Politics Chapter 4 Managing the IT Project Team Chapter 5 Defining IT Projects Chapter 6 Organizing IT Projects Chapter 7 Quality From the Ground Up Chapter 8 Forming the IT Project Team Chapter 9 Planning IT Projects Chapter 10 Managing IT Projects Chapter 11 Tracking IT Projects Chapter 12 Closing Out IT Projects
FGS: Computer Simulation System in Generating Fractals
Authors: Hizmawati Madzin, Roziati Zainuddin
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

Fractal can be represented as an irregular and fragmented geometric shape that can be subdivided in parts, where each part appears to be the same in all ranges of scale. The generation of each fractal is dependent on the approach and algorithm used. Thus it is important to understand the properties of each type of fractals as this will influence the procedure during the generation of fractal. This paper discusses on three types of fractal iteration techniques, which are generator, IFS and formula iteration. Each iteration is supported with fractal algorithm. A system called Fractal Generation System (FGS) is developed to generate fractals by implementing the mentioned iteration techniques. Fractal dimension parameter is an important property which enables the characterization of the, complexity, irregularity and self-similarity of shapes. It is measured here to compare with theoretical value of fractal dimension and verify the accuracy of the fractal simulation.
Boosting for Learning Multiple Classes with Imbalanced Class Distribution
Authors: Yanmin Sun, Mohamed S. Kamel, Yang Wang
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which assume a relatively balanced class distribution and equal misclassification costs. This learning difficulty attracts a lot of research interests. Most efforts concentrate on bi-class problems. However, bi-class is not the only scenario where the class imbalance problem prevails. Reported solutions for bi-class applications are not applicable to multi-class problems. In this paper, we develop a cost-sensitive boosting algorithm to improve the classification performance of imbalanced data involving multiple classes. One barrier of applying the cost-sensitive boosting algorithm to the imbalanced data is that the cost matrix is often unavailable for a problem domain. To solve this problem, we apply Genetic Algorithm to search the optimum cost setup of each class. Empirical tests show that the proposed cost-sensitive boosting algorithm improves the classification performances of imbalanced data sets significantly.
Neural Substrates of Response-based Sequence Learning using fMRI
Authors: Amanda Bischoff-grethe, Kelly M. Goedert, Daniel T. Willingham, Scott T. Grafton
Venue: Journal of Cognitive Neuroscience (2004)

Representation of sequential structure can occur with respect to the order of perceptual events or the order in which actions are linked. Neural correlates of sequence retrieval associated with the order of motor responses were identified in a variant of the serial reaction time task in which training occurred with a spatially incompatible mapping between stimuli and finger responses. After transfer to a spatially compatible version of the task, performance enhancements indicative of learning were only present in subjects required to make finger movements in the same order used during training. In contrast, a second group of subjects performed the compatible task using an identical sequence of stimuli (and different order of finger movements) as in training. They demonstrated no performance benefit, indicating that learning was response based. Analysis was restricted to subjects demonstrating low recall of the sequence structure to rule out effects of explicit awareness. The interaction of group (motor vs. perceptual transfer) with sequence retrieval (sequencing vs. rest) revealed significantly greater activation in the bilateral supplementary motor area, cingulate motor area, ventral premotor cortex, left caudate, and inferior parietal lobule for subjects in the motor group (illustrating successful sequence retrieval at the response level). Retrieval of sequential responses occurs within mesial motor areas and related motor planning areas.
Illusory Contour Perception and Amodal Boundary Completion: Evidence of a Dissociation Following Callosotomy
Authors: Paul M. Corballis, Robert Fendrich, Robert M. Shapley, Michael S. Gazzaniga
Venue: Journal of Cognitive Neuroscience (1999)

A fundamental problem in form perception is how the visual system can link together spatially separated contour fragments to form the percept of a unitary shape. Illusory contours and amodal completion are two phenomena that demonstrate this linking process . In the present study we investigate these phenomena in the divided hemispheres of two callosotomy ("split-brain") patients. The data suggest that dissociable neural mechanisms are responsible for the genera tion of illusory contours and amodal completion. Although both cerebral hemispheres appear to be equally capable of perceiving illusory contours, amodal completion is more readily utilized by the right hemisphere. These results suggest that illusory contours may be attributable to low-level visual processes common to both hemispheres, whereas amodal completion reflects a higher-level, lateralized process.
Overlay Networks Construction for Multilayered Live Media Streaming
Authors: Hui Guo, Kowk-Tung Lo, Chi-Tsun Cheng
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

Live peer-to-peer (P2P) streaming has become a promising approach to broadcasting non-interactive streaming media content from a server to a large number of interested clients. It still faces many challenges, however, such as high churn rate of peer clients, uplink bandwidth constrains of participating peers, and heterogeneity of client capacities. This paper presents LSONet, a collaborative peer-to-peer streaming framework for scalable layer-encoded bit streams. For achieving higher streaming quality and resilient to peer churn, this paper employs a mesh-based data-driven scheme for partnership formation, and proposes tow algorithms, optimal transmission policy (OTP) and graceful degradation scheme (GDS), for multi-layers allocation. Extensive simulations show that LSONet achieves higher quality of service thanks to peer-assisted streaming and layered video coding. Also, through comparison, results show that the system outperforms previous scheme in resource utilization and control overhead.
Probabilistic Internal Privacy Intrusion Detection
Authors: Xiangdong An, Dawn Jutla, Nick Cercone
Venue: Proceedings of the 10th International Database Engineering and Applications Symposium (2006)

Many organizations need to maintain a lot of private data to run their businesses. Private data could be violated by both the inside and the outside intruders. In this paper, we propose a probabilistic method to detect insider privacy intrusion in database systems.
Blindsight after Optic Nerve Injury Indicates Functionality of Spared Fibers
Authors: Stefan Wüst, Erich Kasten, Bernhard A. Sabel
Venue: Journal of Cognitive Neuroscience (2002)

Some patients with lesions in the geniculostriate pathway (GSP) can respond to visual stimuli in the blind field without conscious acknowledgement. The substrate for this "blindsight" is controversial: whether it is the uninjured extrastriate pathway (EXP), which bypasses the lesion site, or residual fibers within damaged visual cortex ("islands of vision"). Using stimulus detection, localization, and spatial summation tasks, we have found blindsight in patients with damage both in the optic nerve (ON) and EXP. The prevalence and functional characteristics of their blindsight are indistinguishable from that in patients with GSP lesions, so blindsight does not require a completely intact EXP. The present findings support the view that a few surviving ON axons within an area of primary damage are sufficient to mediate blindsight: Several combinations of partially intact pathways can transmit information to the extrastriate cortex and the sum of activation of all visual fibers surviving the injury determines if and to what extent blindsight occurs.