ppxscal/embedding_network huggingface dataset:
Objective Evaluation of Pedestrian and Vehicle Tracking on the CLEAR Surveillance Dataset
Authors: Murtaza Taj, Emilio Maggio, Andrea Cavallaro
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

Video object detection and tracking in surveillance scenarios is a difficult task due to several challenges caused by environmental variations, scene dynamics and noise introduced by the CCTV camera itself. In this paper, we analyse the performance of an object detector and tracker based on background subtraction followed by a graph matching procedure for data association. The analysis is performed based on the CLEAR dataset. In particular, we discuss a set of solutions to improve the robustness of the detector in case of various types of natural light changes, sensor noise, missed detection and merged objects. The proposed solutions and various parameter settings are analysed and compared based on 1 hour 21 minutes of CCTV surveillance footage and its associated ground truth and the CLEAR evaluation metrics.
Augmenting Presentation MathML for Search
Authors: Bruce R. Miller, Abdou Youssef
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

The ubiquity of text search is both a boon and bane for the quest for math search. A bane in that user's expectations are high regarding accuracy, in-context highlighting and similar features. Yet also a boon with the availability of highly evolved search engine libraries; Youssef has previously shown how an appropriate `textualization' of mathematics into an indexable form allows standard text search engines to be applied.Furthermore, given sufficiently semantic source forms for the math, such as or Content MathML, the indexed form can be enhanced by co-locating synonyms, aliases and other metadata, thus increasing the accuracy and richness of expression.Unfortunately, Content MathML is not always available, and the conversion from to Presentation MathML (pMML) is too complex to carry out on the fly. Thus, one loses the ability to provide query-specific, fine-grained highlighting within the pMML displayed in search results to the user.Where semantic information is available, however, such as for pMML generated from a richer representation, we propose augmenting the generated pMML with those semantics from which synonyms and other metadata can be reintroduced. Thus, in this paper, we aim to have both the high accuracy introduced by semantics while still obtaining fine-grained highlighting.
Regularization for Regression Models Based on the K-Functional with Besov Norm
Authors: Imhoi Koo, Rhee Man Kil
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper presents a new method of regularization in regression problems using a Besov norm (or semi-norm) acting as a regularization operator. This norm is more general smoothness measure to approximation spaces compared to other norms such as Sobolev and RKHS norms which are usually used in the conventional regularization methods. In our work, we also suggest a new candidate of the regularization parameter, that is, the trade-off between the data fit and the smoothness of the estimation function. Through the simulation for function approximation, we have shown that the suggested regularization method is effective and the estimated values of regularization parameters are close to the optimal values associated with the minimum expected risks.
Balance-dendrogram. A new routine of CoDaPack
Authors: S. Thió-Henestrosa, J. J. Egozcue, V. Pawlowsky-Glahn, L. í. Kovács, G. P. Kovács
Venue: Computers Geosciences (2008)

A statistical analysis of compositional data based on the Aitchison geometry of the simplex requires an appropriate basis for representing the data. A simple and intuitive way of building such a basis employs a sequential binary partition of the compositional vector. The partition, together with some statistical summaries of the coordinates, or balances, can be represented in a dendrogram-type graph. In this paper we introduce an implementation of this methodology inside CoDaPack, which is freeware. An example with real data illustrates the use of the Balance-Dendrogram routine.
HITP: A Transmission Protocol for Scalable High-Performance Distributed Storage
Authors: P. Giacomin, A. Bassi, F. J. Seinstra, T. Kielmann, H. E. Bal
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

In many application and research areas there is a trend towards petascale processing and archiving of scientific measurement results and derived data structures. As a consequence, there is an urgent need for disruptive technologies that revolutionize the manner in which we integrate, coordinate, and distribute computing and storage of vast amounts of data. This paper discusses the INCA architecture, a system that aims at providing a sustainable solution to the management problem of data storage in very large-scale distributed systems. INCA provides a solution where 'intelligence' in a globally scalable system is put in the middleware, where the lower level deals with local problems only, while all other properties are taken care of at the upper layers. In particular, we focus on a new, efficient transport protocol (referred to as HITP) that is specifically designed for bulk data transfer over high-speed (optical) network connections. We present performance results for basic transmission functionality, and show that HITP is capable of achieving higher throughput and lower latency than existing transport protocols.
A Modeling and Assessing Method Based on Bayesian Networks
Authors: Zhi Liu, Jie Jiang
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

In order to give adaptive instruction to the learner, it needs to know what knowledge the learner has and what goals the learner is trying to archive. This paper proposes a method to build a model based on Bayesian networks in order to assess the learner's knowledge level. An overlay student model based on Bayesian networks is presented. This student model built on knowledge relationships with prediction ability is discussed in details. In this model, an assessing method based on Logistic model in IRT with three parameters is provided to evaluate student's performance. A case study in the course of Data Structure is illustrated in this paper.
A Novel Greedy Bayesian Network Structure Learning Algorithm for Limited Data
Authors: Feng Liu, Fengzhan Tian, Qiliang Zhu
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

Existing algorithms for learning Bayesian network (BN) require a lot of computation on high dimensional itemsets, which affects accuracy especially on limited datasets and takes up a large amount of time. To alleviate the above problem, we propose a novel BN learning algorithm MRMRG, Max Relevance and Min Redundancy Greedy algorithm. MRMRG algorithm is a variant of K2 algorithm for learning BNs from limited datasets. MRMRG algorithm applies Max Relevance and Min Redundancy feature selection technique and proposes Local Bayesian Increment (LBI) function according to the Bayesian Information Criterion (BIC) formula and the likelihood property of overfitting. Experimental results show that MRMRG algorithm has much better efficiency and accuracy than most of existing BN learning algorithms when learning BNs from limited datasets.
Robust Automatic Speech Recognition Using PD-MEEMLIN
Authors: Igmar Hernández, Paola García, Juan Nolazco, Luis Buera, Eduardo Lleida
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

This work presents a robust normalization technique by cascading a speech enhancement method followed by a feature vector normalization algorithm. To provide speech enhancement the Spectral Subtraction (SS) algorithm is used; this method reduces the effect of additive noise by performing a subtraction of the noise spectrum estimate over the complete speech spectrum. On the other hand, an empirical feature vector normalization technique known as PD-MEMLIN (Phoneme-Dependent Multi-Enviroment Models based LInear Normalization) has also shown to be effective. PD-MEMLIN models clean and noisy spaces employing Gaussian Mixture Models (GMMs), and estimates a set of linear compensation transformations to be used to clean the signal. The proper integration of both approaches is studied and the final design, PD-MEEMLIN (Phoneme-Dependent Multi-Enviroment Enhanced Models based LInear Normalization), confirms and improves the effectiveness of both approaches. The results obtained show that in very high degraded speech PD-MEEMLIN outperforms the SS by a range between 11.4% and 34.5%, and for PD-MEMLIN by a range between 11.7% and 24.84%. Furthemore, in moderate SNR, i.e. 15 or 20 dB, PD-MEEMLIN is as good as PD-MEMLIN and SS techniques.
Nanotwin formation and its physical properties and effect on reliability of copper interconnects
Authors: Di Xu, Vinay Sriram, Vidvuds Ozolins, Jenn-Ming Yang, K. N. Tu, Gery R. Stafford, Carlos Beauchamp, Inka Zienert, Holm Geisler, Petra Hofmann, Ehrenfried Zschech
Venue: Microelectronic Engineering (2008)

Ultra-fine grained copper with a large amount of nano-scale twin boundaries has high mechanical strength and maintains normal electrical conductivity. The combination of these properties may lead to promising applications in future Si microelectronic technology, especially as interconnect material for air-gap and free-standing copper technologies. Based on first principles calculations of total energy and in-situ stress measurements, high stress followed by stress relaxation during the Cu film deposition seems to have contributed to nanotwin formation. Nanoindentation studies have shown a larger hardness for copper with a higher nanotwin density. The effect of Cu nanotwin boundaries on grain growth was investigated by scanning electron microscopy (SEM), electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM). The presence of a high density of nanotwin boundaries may improve the reliability of Cu interconnects.
Open Educational Resources: Inquiring into Author Reuse Behaviors
Authors: Lisa Petrides, Lilly Nguyen, Anastasia Kargliani, Cynthia Jimes
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

For teachers and learners, the proliferation of open educational resources (OER) in combination with advances in information technologies has meant centralized access to materials and the possibility of creating, using, and reusing OER globally, collaboratively, and across multiple disciplines. Through an examination of a community of author users of the OER portal Connexions, this article explores OER reuse behaviors and factors contributing to and hindering those behaviors. As such, the article sheds light on how OER can be sustained and continuously improved, with an emphasis on the reuse of dynamic, relevant, and high quality materials over time.
Anonymisation of Swedish Clinical Data
Authors: Dimitrios Kokkinakis, Anders Thurin
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

There is a constantly growing demand for exchanging clinical and health-related information electronically. In the era of the Electronic Health Record the release of individual data for research, health care statistics, monitoring of new diagnostic tests and tracking disease outbreak alerts are some of the areas in which the protection of (patient) privacy has become an important concern. In this paper we present a system for automatic anonymisation of Swedish clinical free text, in the form of discharge letters, by applying generic named entity recognition technology.
Balancing Quantification and Obliviousness in the Design of Aspect-Oriented Frameworks
Authors: Linda Seiter
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

Aspect-oriented languages support modular programming by providing powerful referencing mechanisms that allow programmers to make quantified assertions about their programs. An aspect selects a set of program elements using a reference called a pointcut. An aspect also defines advice methods that transform the control flow surrounding the selected program elements. It is difficult, however, to define a reusable aspect when the advice methods require access to the local context of the program elements, as the bindings of the advice parameters may vary in each application. This leads to a breakdown of the modularity, quantification and obliviousness properties of aspect-oriented programming. This paper presents a model for modularizing the crosscutting references found in aspect-oriented frameworks. An extension to AspectJ is presented that utilizes Java annotations to implement polymorphic advice method parameters.
Confidently Cutting a Cake into Approximately Fair Pieces
Authors: Jeff Edmonds, Kirk Pruhs, Jaisingh Solanki
Venue: Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management (2008)

We give a randomized protocol for the classic cake cutting problem that guarantees approximate proportional fairness, and with high probability uses a linear number of cuts.
HAPADEP: Human-Assisted Pure Audio Device Pairing
Authors: Claudio Soriente, Gene Tsudik, Ersin Uzun
Venue: Proceedings of the 11th international conference on Information Security (2008)

The number and diversity of personal electronic gadgets have been steadily increasing but there has been fairly little progress in secure pairing of such devices. The pairing challenge revolves around establishing on-the-fly secure communication without any trusted (on- or off-line) third parties between devices that have no prior association. One basic approach to counter Man-in-the-Middle (MiTM) attacks in such setting is to involve the user in the pairing process. Previous research yielded some interesting secure pairing techniques, some of which ask too much of the human user, while others assume availability of specialized equipment (e.g., wires, photo or video cameras) on personal devices. Furthermore, all prior methods assumed an established insecure channel over a common digital (human-imperceptible) communication medium, such as infrared, 802.11 or Bluetooth.In this paper we introduce a very simple technique called HAPADEP (Human-Assisted Pure Audio Device Pairing). HAPADEP uses the audio channel to exchange both data and verification information among devices without requiring any other means of common electronic communication. Despite its simplicity, a number of interesting issues arise in the design of HAPADEP. We discuss design and implementation highlights as well as usability features and limitations.
Proposing a speech to gesture translation architecture for Spanish deaf people
Authors: R. San-Segundo, J. M. Montero, J. Macías-Guarasa, R. Córdoba, J. Ferreiros, J. M. Pardo
Venue: Journal of Visual Languages and Computing (2008)

This article describes an architecture for translating speech into Spanish Sign Language (SSL). The architecture proposed is made up of four modules: speech recognizer, semantic analysis, gesture sequence generation and gesture playing. For the speech recognizer and the semantic analysis modules, we use software developed by IBM and CSLR (Center for Spoken Language Research at University of Colorado), respectively. Gesture sequence generation and gesture animation are the modules on which we have focused our main effort. Gesture sequence generation uses semantic concepts (obtained from the semantic analysis) associating them with several SSL gestures. This association is carried out based on a number of generation rules. For gesture animation, we have developed an animated agent (virtual representation of a human person) and a strategy for reducing the effort in gesture animation. This strategy consists of making the system automatically generate all agent positions necessary for the gesture animation. In this process, the system uses a few main agent positions (two or three per second) and some interpolation strategies, both issues previously generated by the service developer (the person who adapts the architecture proposed in this paper to a specific domain). Related to this module, we propose a distance between agent positions and a measure of gesture complexity. This measure can be used to analyze the gesture perception versus its complexity. With the architecture proposed, we are not trying to build a domain independent translator but a system able to translate speech utterances into gesture sequences in a restricted domain: railway, flights or weather information.
Distance-based indexing and its applications in bioinformatics
Authors: Daniel P. Miranker
Venue:  (2007)

Distance-based indexing is a general solution to the problem of searching based on similarity of complex data types. Distances between pairs of data objects are specified by a metric function, which is positive definite, symmetric and satisfies the triangle inequality. Distance-based indexing is exploited in many data intensive applications, such as multimedia and biological databases. This dissertation concerns distance-based indexing in the context of the MoBIoS (Molecular Biology Information System) project, a next generation DBMS aimed at bioinformatics applications. The three primary contributions of this dissertation include evaluation and improvement of existing distance-based index structures, a pivot space model for the pivot selection problem of distance-based indexing and the MoBIoS Index software package. For the first part, we designed a bi-directional construction algorithm for Metric Tree (M-tree). It increased the construction speed and improved the query performance. Then, we conducted a comparative analysis of the performance of M-tree, General Hyper-plane Tree (GHT) and Vantage Point Tree (VPT) on biological work loads, and VPT turned out to be the optimal choice. Further, we designed better heuristics for pivot selection and partition of VPT. Superior to multi-dimensional indexing in its generality, distance-based indexing is difficult by virtue that no coordinate structure is available and thus many mathematical tools in Rn cannot be applied. A common method used is to map the metric space into Rn and then apply geometric methods. Summarizing this method, we propose the pivot space model, which demonstrates the validity of tackling distance-based problems in Rn. Further, we study distance-based indexing from the perspective of dimension reduction. We prove that the only form of dimension reduction leading to performance gain for distance-based indexing is pivot selection, which does not create new dimensions. To adapt general dimension reduction techniques to distance-based problems, we propose a heuristic that approximates the dimensions created by dimension reduction. As a demonstration, a dimension reduction algorithm and a method to estimate the intrinsic dimension of data are proposed based on Principal Component Analysis (PCA). These ideas are evaluated on a test suite consisting of synthetic and real workloads. The MoBIoS Index was released in 2006. It supports similarity queries for user defined data types and distance functions. It has been used to build several biological application.
Confidence-Compensating Privacy Protection
Authors: Piotr Cofta
Venue: Proceedings of the 2008 Sixth Annual Conference on Privacy, Security and Trust (2008)

The particularly acute problem in privacy protection is to provide such a protection beyond the original disclosure of personal information. There, the need for privacy is strongly related to the confidence in the goodwill of the party that receives such information. In the absence of such a confidence, the disclosure should be limited. However, putting excessive constrains on the disclosure itself can have a damaging effect on the relationship. In order to minimize the potential damage, limitations to the extent of a disclosure should be deployed sparsely, with its strength and direction adjusted to the extent of actual lack of confidence. This paper proposes the flexible strategy for privacy protection that takes into account the lack of perceived confidence. The strategy determines three orthogonal dimensions that can be used to classify various privacy-enhancing tools and links those dimensions with individual’s structure of beliefs regarding confidence. This allows to provide the simple decision-making tools that allows to determine the best minimum privacy protection for a given case.
Pair programming: what's in it for me?
Authors: Andrew Begel, Nachiappan Nagappan
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Pair programming is a practice in which two programmers work collaboratively at one computer on the same design, algorithm, or code. Prior research on pair programming has primarily focused on its evaluation in academic settings. There has been limited evidence on the use, problems and benefits, partner selection, and the general perceptions towards pair programming in industrial settings. In this paper we report on a longitudinal evaluation of pair programming at Microsoft Corporation. We find from the results of a survey sent to a randomly selected 10% of engineers at Microsoft that 22% pair program or have pair programmed in the past. Using qualitative analysis, we performed a large-scale card sort to group the various benefits and problems of pair programming. The biggest perceived benefits of pair programming were the introduction of fewer bugs, spreading code understanding, and producing overall higher quality code. The top problems were cost-efficiency, (work time) scheduling problems, and personality conflicts. Most engineers preferred a partner who had complementary skills to their own, who was flexible and had good communication skills.
The Influence of the Risk Functional in Data Classification with MLPs
Authors: Luís M. Silva, Mark Embrechts, Jorge M. Santos, J. Marques Sá
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

We investigate the capability of multilayer perceptrons using specific risk functionals attaining the minimum probability of error (optimal performance) achievable by the class of mappings implemented by the multilayer perceptron (MLP). For that purpose we have carried out a large set of experiments using different risk functionals and datasets. The experiments were rigorously controlled so that any performance difference could only be attributed to the different risk functional being used. Statistical analysis was also conducted in a careful way. From the several conclusions that can be drawn from our experimental results it is worth to emphasize that a risk functional based on a specially tuned exponentially weighted distance attained the best performance in a large variety of datasets. As to the issue of attaining the minimum probability of error we also carried out classification experiments using non-MLP classifiers that implement complex mappings and are known to provide the best results until this date. These experiments have provided evidence that at least in many cases, by using an adequate risk functional, it will be possible to reach the optimal performance.