ppxscal/embedding_network huggingface dataset:
Joint Boosting Feature Selection for Robust Face Recognition
Authors: Rong Xiao, Wujun Li, Yuandong Tian, Xiaoou Tang
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framework is proposed to address this problem. In our framework, 3D face models are used to synthesize a huge database of realistic face images which covers wide appearance variations of faces due to various pose, illumination, and expression changes. A novel feature selection algorithm which we call Joint Boosting is developed to extract discriminative face features using this massive database. The major contributions of this paper are: (1) With the help of 3D face models, a massive database of realistic virtual face images is generated to achieve robust feature selection; (2)Because the huge database covers a wide range of face variations, our feature selection procedure only needs to be trained once, and the selected feature set can be generalized to other face database without re-training; (3) We propose a new learning algorithm, Joint Boosting Algorithm, which is effective and efficient in learning directly from a massive database without having to convert face images to intra-personal and extra-personal difference images. This property is important for applying our algorithm to other general pattern recognition problems. Experimental results show that our method significantly improves recognition performance.
ICA-Based Potential Significant Feature Extraction for Market Forecast
Authors: Ling Huang, Jinhong Zhong
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)

Most of market demands are greatly dynamically changed such as in finance, industries and etc.. In order to adapt to the highly dynamic changes of market and reduce cost and risk, we need to develop effective management strategies based on accurate market demand forecast. Many of the traditional forecasting methods, such as the neural network, ARIMA, which based on historical data, cannot find out the hidden remarkable features behind the data, thereby affecting the accuracy of forecasting. In this paper, ICA as one of the most popular signal decomposition technologies in recent years is introduced to excavate the potential information of market for better prediction of dynamic changes in market demand and mining of margin customer, where ICA plays an important role of preprocessing. The experiments show that the prediction based on ICA preprocessing is superior to direct prediction by neural network, and successful to excavate potential customers for better market directing. In addition, we also address the essential difference of dimension reduction using PCA and ICA, show that these two approaches are different at the aspect of sensitivity to dimensions although they both are pre-processing methods of dynamic data, even if the accumulative contribution rate of ICA is 7.4% less than that of PCA, the former still attains the same prediction results as the latter.
Feature Modelling of PCA Difference Vectors for 2D and 3D Face Recognition
Authors: Chris McCool, Jamie Cook, Vinod Chandran, Sridha Sridharan
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

This paper examines the the effectiveness of feature modelling to conduct 2D and 3D face recognition. In particular, PCA difference vectors are modelled using Gaussian Mixture Models (GMMs) which describe Intra-Personal (IP) and Extra-Personal (EP) variations. Two classifiers, an IP and IPEP classifier, are formed using these GMMs and their performance is compared to that of the Mahalanobis cosine metric (MahCosine). The best results for the 2D and 3D face modalities are obtained with the IP and IPEP classifiers respectively. The multi-modal fusion of these two systems provided consistent performance improvement across the FRGC database v2.0.
Mobile Augmented Reality System Architecture for Ubiquitous e-Learning
Authors: Jayfus T. Doswell, M. Brian Blake, Jerome Butcher-Green
Venue: Proceedings of the Fourth IEEE International Workshop on Wireless, Mobile and Ubiquitous Technology in Education (2006)

Mobile Augmented Reality Systems (MARS) e-learning has the potential to provide continuous, context-based, and autonomous instruction to human learners anytime, anyplace, and at any-pace. MARS e-learning enables mobility for the learner and hands free human computer interactivity. Advances to MARS based learning provides the advantage of a natural human-computer interface, flexible mobility, and context-aware instruction allowing learners to develop psychomotor skills while interacting with their natural environment with augmented perceptual cues. These perceptual cues combining multi-modal animation, graphics, text, video, and voice along with empirical instructional techniques can elegantly orchestrate a mobile instructional tool. The challenge, however, is building a MARS e-learning tool with capabilities for adapting to various learning environments while also considering the cultural, geographical, and other contexts about the learner. This paper discusses a novel system/software architecture, CAARS, for developing context-aware mobile augmented reality instructional systems.
Quantification of Intermarket Influence Based on the Global Optimization and Its Application for Stock Market Prediction
Authors: C. D. Tilakaratne, M. A. Mammadov, C. P. Hurst
Venue: Proceedings of the International Workshop on on Integrating AI and Data Mining (2006)

This study investigates how intermarket influences can be used to help the prediction of the direction (up or down) of the next day's Close price of the Australian All Ordinary Index (AORD). First, intermarket influences from the potential influential markets on the AORD are quantified by assigning weights for all influential markets. The weights were defined as a solution to an optimization problem which aims to maximise rank correlation between the current day's relative return of the AORD and the weighted sum of lagged relative returns of the potential influential markets. Then, the next day's relative return of the AORD is predicted by applying the neural networks as a classifier. Two different scenarios were compared: 1) using the current day's relative returns of different sets of influential markets as separate inputs; and, 2) using only the weighted sum of these relative returns as a "combined market". The results revealed that the second approach provides better predictions in all cases. This shows the effectiveness of the proposed approach for quantifying intermarket influences and the potential of using the "weighted combined markets" for the prediction.
Validation and verification of social processes within agent-based computational organization models
Authors: Levent Yilmaz
Venue: Computational Mathematical Organization Theory (2006)

The use of simulation modeling in computational analysis of organizations is becoming a prominent approach in social science research. However, relying on simulations to gain intuition about social phenomena has significant implications. While simulations may give rise to interesting macro-level phenomena, and sometimes even mimic empirical data, the underlying micro and macro level processes may be far from realistic. Yet, this realism may be important to infer results that are relevant to existing theories of social systems and to policy making. Therefore, it is important to assess not only predictive capability but also explanation accuracy of formal models in terms of the degree of realism reflected by the embedded processes. This paper presents a process-centric perspective for the validation and verification (V V) of agent-based computational organization models. Following an overview of the role of V V within the life cycle of a simulation study, emergent issues in agent-based organization model V V are outlined. The notion of social contract that facilitates capturing micro level processes among agents is introduced to enable reasoning about the integrity and consistency of agent-based organization designs. Social contracts are shown to enable modular compositional verification of interaction dynamics among peer agents. Two types of consistency are introduced: horizontal and vertical consistency. It is argued that such local consistency analysis is necessary, but insufficient to validate emergent macro processes within multi-agent organizations. As such, new formal validation metrics are introduced to substantiate the operational validity of emergent macro-level behavior.
Static and dynamic models of biological networks: Research Articles
Authors: Ashish Bhan, Eric Mjolsness
Venue: Complexity (2006)

We consider static and dynamic approaches to the specification of probability distributions on graphs, consistent with desired statistical properties such as degree distributions, for use in modeling biological networks. In the static approach we develop analytical approximations to the Hamiltonian and partition functions. In the dynamic approach, we use a stochastic parameterized grammar to construct an evolutionary tree in which the nodes represent elements such as genes or cells and the links represent inheritance relations between the nodes. The grammar then constructs a network based on the feature vectors of the nodes in the tree. &copy; 2006 Wiley Periodicals, Inc. Complexity 11:57&ndash;63, 2006This paper was submitted as an invited paper resulting from the &ldquo;Understanding Complex Systems&rdquo; conference held at the University of Illinois&ndash;Urbana Champaign, May 2005
Reducing barriers for e-business in SME's through an open service oriented infrastructure
Authors: Mikkel Hippe Brun, Christian Lanng
Venue: Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet (2006)

The Danish Ministry of Science, Technology and Innovation wishes to establish the necessary services needed in a national service oriented architecture. A key piece of technology in this vision is a hierarchy of addressing services based on registries.The ministry will register all public sector institutions with their UBL-based1 invoice services in a master registry. This guarantees a critical mass of public sector institutions and offers a good value proposition to the SME's. Not only can they send all invoices to the public sector electronically but they also have the ability to send electronic invoices to other private companies registered in the registry.The ministry believes that this solution will demonstrate the advantages of a service oriented architecture [1] and infrastructure based on registries and that this demonstration will generate the broad use of registries for other services.The proposed solution [2] consists of elements normally associated with a web service architecture. What differentiates this proposal is not the content but the approach to lowering barriers by limiting implementation choices and ensuring a critical mass of service providers.
An Event-related Potential Study of Selective Auditory Attention in Children and Adults
Authors: Donna Coch, Lisa D. Sanders, Helen J. Neville
Venue: Journal of Cognitive Neuroscience (2005)

In a dichotic listening paradigm, event-related potentials (ERPs) were recorded to linguistic and nonlinguistic probe stimuli embedded in 2 different narrative contexts as they were either attended or unattended. In adults, the typical N1 attention effect was observed for both types of probes: Probes superimposed on the attended narrative elicited an enhanced negativity compared to the same probes when unattended. Overall, this sustained attention effect was greater over medial and left lateral sites, but was more posteriorly distributed and of longer duration for linguistic as compared to nonlinguistic probes. In contrast, in 6- to 8-year-old children the ERPs were morphologically dissimilar to those elicited in adults and children displayed a greater positivity to both types of probe stimuli when embedded in the attended as compared to the unattended narrative. Although both adults and children showed attention effects beginning at about 100 msec, only adults displayed left-lateralized attention effects and a distinct, posterior distribution for linguistic probes. These results suggest that the attentional networks indexed by this task continue to develop beyond the age of 8 years.
Segmentation of medical images under topological constraints
Authors: Florent Segonne
Venue:  (2006)

Major advances in the field of medical imaging over the past two decades have provided physicians with powerful, non-invasive techniques to probe the structure, function, and pathology of the human body. This increasingly vast and detailed amount of information constitutes a great challenge for the medical imaging community, and requires significant innovations in all aspect of image processing. To achieve accurate and topologically-correct delineations of anatomical structures from medical images is a critical step for many clinical and research applications. In this thesis, we extend the theoretical tools applicable to the segmentation of images under topological control, apply these new concepts to broaden the class of segmentation methodologies, and develop generally applicable and well-founded algorithms to achieve accurate segmentations of medical images under topological constraints. First, we introduce a digital concept that offers more flexibility in controlling the topology of digital segmentations. Second, we design a level set framework that offers a subtle control over the topology of the level set components. Our method constitutes a trade-off between traditional level sets and topology-preserving level sets. Third, we develop an algorithm for the retrospective topology correction of 3D digital segmentations. Our method is nested in the theory of Bayesian parameter estimation, and integrates statistical information into the topology correction process. In addition, no assumption is made on the topology of the initial input images. Finally, we propose a genetic algorithm to accurately correct the spherical topology of cortical surfaces. Unlike existing approaches, our method is able to generate several potential topological corrections and to select the maximum-a-posteriori retessellation in a Bayesian framework. Our approach integrates statistical, geometrical, and shape information into the correction process, providing optimal solutions relatively to the MRI intensity profile and the expected curvature. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Supply Chain Quality Control Decision under Different Product Structures
Authors: Cuihua Zhang, Guangshu Chang, Haibin Yu
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

In designing a supply chain, product structure has been proved to be an important factor affecting supply chain quality control level decision of the buyers and the suppliers. In this article, product structure is divided into separable and non-separable sorts. And then principal agent models for them are set up accordingly. Classic control theory is used to solve the models. Results under different product structures are compared. Under non-separable product structure, the buyer's decision on quality evaluation level is higher than that under separable product structure, and correspondingly the buyer's income is higher. And the effect of product structure on supply chain quality control decision is analyzed. At last simulation calculation is done.
Understanding misalignment and cascading change of ERP implementation: a stage view of process analysis
Authors: Hsiao-Lan Wei, Eric T. G. Wang, Pei-Hung Ju
Venue: European Journal of Information Systems (2005)

When adopting an enterprise resource planning (FRP) system, experiencing misalignments between the functionality offered by the package and that required by the firm is common. Implementing an ERP package often necessitates disruptive organizational change, and the outcome of implementation is largely determined by the resolution of misalignment problems. This study draws upon data from a case study to understand the misalignments of ERP adoption and the associated change dynamics from a stage view. The results reveal that industry-, company-, and regulation-specific misalignments often occurred in the chartering phase; misalignments of input, control, data, process, output, and schedule are the major problems in the project phase; misalignments of information and new business requirements are the main concerns in the shakedown phase and onward and upward phase. The cascading effects of misalignments and change actions are illustrated, the misalignment resolution strategies examined, and the implications discussed.
Dialogue-Based Authoring of Units of Learning
Authors: Dietmar Janetzko
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Authoring learning content along with specifying its relationship to pedagogical scenarios is a tedious and error-prone task. This paper describes DBAT-LD (Dialogue-Based Authoring of Learning Designs), which is a chat bot (natural language dialogue system) that interacts with authors of units of learning and secures the content of the dialogue in an XML-based target format of choice. DBAT-LD can be geared towards different specifications thereby contributing to interoperability in e-learning. In the case of IMS-LD, DBAT-LD elicits and reconstructs an account of learning activities along with the pedagogical support activities [1] and delivers a Level A description of a unit of learning.
Expertise in essay scoring
Authors: Edward W. Wolfe, Michael Ranney
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

Achieving levels of reliability that allow large-scale essay assessments to be used to guide educational policy is a major hurdle for test developers. Previous studies have shown that one influential source of measurement error associated with essay scores is rater idiosyncracies [Engelhard 1994]. Although the literature dealing with scoring cognition is not conclusive about why some scorers are more consistent than others, it offers some insight into variables that may account for individual differences in scoring competence [Pula & Huot 1993; Wolfe & Feltovich 1994].
Aging and Recognition Memory: Changes in Regional Cerebral Blood Flow Associated with Components of Reaction Time Distributions
Authors: David J. Madden, Lawrence R. Gottlob, Laura L. Denny, Timothy G. Turkington, James M. Provenzale, Thomas C. Hawk, R. Edward Coleman
Venue: Journal of Cognitive Neuroscience (1999)

We used H215O positron emission tomography (PET) to measure age-related changes in regional cerebral blood flow (rCBF) during a verbal recognition memory task. Twelve young adults (20 to 29 years) and 12 older adults (62 to 79 years) participated. Separate PET scans were conducted during Encoding, Baseline, and Retrieval conditions. Each of the conditions involved viewing a series of 64 words and making a two-choice response manually. The complete reaction time (RT) distributions in each task condition were characterized in terms of an ex-Gaussian model (convolution of exponential and Gaussian functions). Parameter estimates were obtained for the mean of the exponential component (&tau;), representing a task-specific decision process and the mean of the Gaussian component (&mu;), representing residual sensory coding and response processes. Independently of age group, both &mu; and &tau; were higher in the Encoding and Retrieval conditions than in the Baseline condition, and &tau; was higher during Retrieval than during Encoding. Age-related slowing in task performance was evident primarily in &mu;. For young adults, rCBF activation in the right prefrontal cortex, in the Retrieval condition, was correlated positively with &mu; but not with &tau;. For older adults, rCBF changes (both increases and decreases) in several cortical regions were correlated with both &mu; and &tau;. The data suggest that the attentional demands of this task are relatively greater for older adults and consequently lead to the recruitment of additional neural systems during task performance.
Effectively Combining Software Verification Strategies: Understanding Different Assumptions
Authors: David Owen, Dejan Desovski, Bojan Cukic
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

In this paper we describe an experiment in which inconsistent results between two tools for testing formal models (and a third used to determine which of the two was correct) led us to a more careful look at the way each tool was being used and a clearer understanding of the output of the tools. For the experiment, we created error-seeded versions of an SCR specification representing a real-world personnel access control system. They were checked using the model checker SPIN and Lurch, our random testing tool for finite-state models. In one case a property violation was detected by Lurch, an incomplete tool, but missed by SPIN, a model checking tool designed for complete verification. We used the SCR Toolset and the Salsa invariant checker to determine that the violation detected by Lurch was indeed present in the specification. We then looked more carefully at how we were using SPIN in conjunction with the SCR Toolset and, eventually, made adjustments so that SPIN also detected the property violation initially detected only by Lurch. Once it was clear the tools were being used correctly and would give consistent results, we did an experiment to determine how they could be combined to optimize completeness and efficiency. We found that combining tools made it possible to verify the specifications faster and with much less memory in most cases.
Scan-Based SoC Test Using Space / Time Pattern Compaction Schemes
Authors: C. Galke, U. Gatzschmann, H. T. Vierhaus
Venue: Proceedings of the 9th EUROMICRO Conference on Digital System Design (2006)

The ever-increasing complexity of Systems on a Chip (SoCs) has driven scan-based logic test technologies to their limits. Built-in self-test is one possible solution to overcome the problem. However, externally controlled test procedures that allow the re-use of existing testers and adaption to changing patterns seem to gain a higher level of industrial acceptance. Then a high degree of test pattern compaction withoutsacrificing test coverage is essential. This paper describes a versatile pattern compaction scheme that is independent from special ATPG tools, can be optimized for either hard-to-test versus large circuits and can even accommodate bit settings in LFSR outputs.
AdapTex: contextually adaptive text entry for mobiles
Authors: Mark D. Dunlop, Andrew Glen, Sunil Motaparti, Sanjay Patel
Venue: Proceedings of the 8th conference on Human-computer interaction with mobile devices and services (2006)

This demonstration introduces AdapTex: a new text entry system that suggests words and phrases to the user based on the current working context on the device, the user's history on the device and an initial corpus analysis. User studies show that AdapTex speeds up text entry while reducing errors.
Building objects out of Plato: applying philosophy, symbolism, and analogy to software design
Authors: Ray Giguette
Venue: Communications of the ACM (2006)

If we analyze a program as we do a story, we might ask: "What is the author really saying?"