ppxscal/embedding_network huggingface dataset:
Structural Construction for On-Line Mathematical Formulae Recognition
Authors: Daniel Průša, Václav Hlaváč
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

We present a method for on-line mathematical formulae recognition based on the structural construction paradigm and two-dimensional grammars. In general, this approach can be successfully used in the analysis of inputs composed of objects that exhibit rich structural relations. An important benefit of the structural construction is in not treating symbols segmentation and structural analysis as two separate processes which allows the system to perform segmentation in the context of the whole formula structure --- this helps to solve arising ambiguities more reliably. We show that the proposed method can be effectively implemented and practically used.
Optimal Cryptographic Hardness of Learning Monotone Functions
Authors: Dana Dachman-Soled, Homin K. Lee, Tal Malkin, Rocco A. Servedio, Andrew Wan, Hoeteck Wee
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

A wide range of positive and negative results have been established for learning different classes of Boolean functions from uniformly distributed random examples. However, polynomial-time algorithms have thus far been obtained almost exclusively for various classes of monotone functions, while the computational hardness results obtained to date have all been for various classes of general (nonmonotone) functions. Motivated by this disparity between known positive results (for monotone functions) and negative results (for nonmonotone functions), we establish strong computational limitations on the efficient learnability of various classes of monotone functions.We give several such hardness results which are provably almost optimal since they nearly match known positive results. Some of our results show cryptographic hardness of learning polynomial-size monotone circuits to accuracy only slightly greater than $1/2 + 1/\sqrt{n}$; this accuracy bound is close to optimal by known positive results (Blum et al., FOCS '98). Other results show that under a plausible cryptographic hardness assumption, a class of constant-depth, sub-polynomial-size circuits computing monotone functions is hard to learn; this result is close to optimal in terms of the circuit size parameter by known positive results as well (Servedio, Information and Computation '04). Our main tool is a complexity-theoretic approach to hardness amplification via noise sensitivity of monotone functions that was pioneered by O'Donnell (JCSS '04).
Recognition of ECoG in BCI Systems Based on a Chaotic Neural Model
Authors: Ruifen Hu, Guang Li, Meng Hu, Jun Fu, Walter J. Freeman
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

For the practical use of brain-computer interface systems, one of the most significant problems is the generalizing ability of the classifiers, since the states of both people and instruments are altering as time goes on. In this paper, a novel chaotic neural network termed KIII model, is introduced to classify single-trial ECoG during motor imagery, acquired in two different sessions. Then, by comparing with other three traditional classifiers, KIII model shows a greater ability to generalize, which demonstrates that KIII model is an effective tool for brain-computer interfaces systems.
Morphological Haar Wavelet-Based Purification of Rotor Center's Orbit
Authors: Yong Lin, Xiaojun Zhou, Wenbin Zhang, Xianyong Yang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Considering data acquisition characteristics of vibration signals of rotating machinery, a new rotor orbit purification method using morphological Haar wavelet is proposed. With this method, noise can be eliminated and purified rotor center's orbits can be obtained following filtration of vibration signals by a combination of decomposition and reconstruction based on morphological Haar wavelet, without requiring consideration of the rotor's vibration spectrum characteristics and neither any prior experience in rotor fault treatment, actual practice have proved the effectiveness of this method. Compared with other methods, this way is more practicable as its morphology wavelets are more effective, its algorithm more simple, calculation and on-site application more facile.
Novelty detection in blind steganalysis
Authors: Tomáš Pevný, Jessica Fridrich
Venue: Proceedings of the 10th ACM workshop on Multimedia and security (2008)

It is generally believed that a blind steganalyzer trained on sufficiently many diverse steganographic algorithms will become universal in the sense that it will generalize to previously unseen (novel) stego methods. While this is a partially correct statement if the embedding mechanism of the novel method resembles some of the methods on which the classifier was trained, we demonstrate that if the classifier is presented with stego images produced by a completely different embedding mechanism, it may fail to detect the images as stego even for an otherwise fairly easily detectable method. Motivated by this observation, we explore two approaches for construction of universal steganalyzers - one-class and one-against-all classifiers. Their advantages and disadvantages are discussed and performance compared on a wide variety of steganographic algorithms. One-against-all classifiers have generally better performance than approaches based on characterizing just the class of covers but they may fail catastrophically on previously unseen stego algorithms. One-class methods are less likely to fail to detect unknown stego algorithms but have lower overall detection accuracy on known stego methods. The suitability of each approach thus depends on the application.
Efficient Execution of Small (Single-Tuple) Transactions in Main-Memory Databases
Authors: Heine Kolltveit, Svein-Olaf Hvasshovd
Venue: Proceedings of the 12th East European conference on Advances in Databases and Information Systems (2008)

Various applications impose different transactional loads on databases. For example for telecommunication systems, online games, sensor networks, and trading systems, most of the database load consists of single-tuple reads and single-tuple writes. In this paper, approaches to handle these single-tuple transactions in main-memory systems are presented. The protocols are evaluated by simulation and verified by statistical analysis. The results show that 70 - 150% more transactions can be executed while keeping response times low using the new approach, compared to a state-of-the-art protocol.
Automatic Transcription of Lithuanian Text Using Dictionary
Authors: Mantas Skripkauskas, Laimutis Telksnys
Venue: Informatica (2006)

There is presented a technique of transcribing Lithuanian text into phonemes for speech recognition. Text-phoneme transformation has been made by formal rules and the dictionary. Formal rules were designed to set the relationship between segments of the text and units of formalized speech sounds - phonemes, dictionary - to correct transcription and specify stress mark and position. Proposed the automatic transcription technique was tested by comparing its results with manually obtained ones. The experiment has shown that less than 6&percnt; of transcribed words have not matched.
Using Pseudo-Relevance Feedback to Improve Image Retrieval Results
Authors: Mouna Torjmen, Karen Pinel-Sauvagnat, Mohand Boughanem
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

In this paper, we propose a pseudo-relevance feedback method to deal with the photographic retrieval and medical retrieval tasks of ImageCLEF 2007. The aim of our participation to ImageCLEF is to evaluate a combination method using both english textual queries and image queries to answer to topics. The approach processes image queries and merges them with textual queries in order to improve results.A first set of expirements using only textual information does not allow to obtain good results. To process image queries, we used the FIRE system to sort similar images using low level features, and we then used associated textual information of the top images to construct a new textual query. Results showed the interest of low level features to process image queries, as performance increased compared to textual queries processing.Finally, best results were obtained combining the results lists of textual queries processing and image queries processing with a linear function.
Some Theorems on Planar Mappings
Authors: Gohar M. Kyureghyan, Alexander Pott
Venue: Proceedings of the 2nd international workshop on Arithmetic of Finite Fields (2008)

A mapping $f:{\mathbb{F}}_p^n\to {\mathbb{F}}_p^n$ is called planar if for every nonzero $a \in {\mathbb{F}}_p^n$ the difference mapping D f,a : x ¿f(x + a) ¿ f(x) is a permutation of ${\mathbb{F}}_p^n$. In this note we prove that two planar functions are CCZ-equivalent exactly when they are EA-equivalent. We give a sharp lower bound on the size of the image set of a planar function. Further we observe that all currently known main examples of planar functions have image sets of that minimal size.
A portable runtime interface for multi-level memory hierarchies
Authors: Patrick M. Hanrahan
Venue:  (2008)

The efficient use of a machine's memory system and parallel processing resources has become one of the most important challenges in program optimization. Moreover, efficient use of the memory hierarchy is increasingly important because of the power cost of data transfers through the system. Architecture trends are leading to large scale parallelism using simpler cores and progressively deeper and complex memory hierarchies. These new architecture designs have improved power characteristics and can offer large increases in performance, but traditional programming techniques are inadequate for these architectures.In this dissertation, we explore a programming language and runtime system for making efficient use of the memory hierarchy and parallel processing resources. This dissertation provides an overview of Sequoia, a programming language we have developed at Stanford to facilitate the development of memory hierarchy aware parallel programs that remain portable across modern machines featuring different memory hierarchy configurations. Sequoia abstractly exposes hierarchical memory in the programming model and provides language mechanisms to describe communication vertically through the machine and to localize computation to particular memory locations within it.This dissertation presents a platform independent runtime interface for moving data and computation through parallel machines with multi-level memory hierarchies. We show that this interface can be used as a compiler target for the Sequoia language and compiler, and can be implemented easily and efficiently on a variety of platforms. The interface design allows us to compose multiple runtimes, achieving portability across machines with multiple memory levels. We demonstrate portability of Sequoia programs across machines with two memory levels with runtime implementations for multi-core/SMP machines, the STI Cell Broadband Engine, a distributed memory cluster, and disk systems. We also demonstrate portability across machines with multiple memory levels by composing runtimes and running on a cluster of SMP nodes, out-of-core algorithms on a Sony Playstation 3 pulling data from disk, and a cluster of Sony Playstation 3's. All of this is done without any source level modifications to the Sequoia program. With this uniform interface, we achieve good performance for our applications and maximize bandwidth and computational resources on these system configurations.
Business process interoperability: extended abstract
Authors: Amit K. Chopra
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: doctoral mentoring program (2008)

A primary challenge for Computer Science is devising suitable abstractions for a given application domain so that solutions may be assembled and analyzed at the level of the domain, that is, by using primitives of the domain. For example, in personal finance, deposit and withdraw are primitives, not add and subtract. Our interest lies in the domain of business processes. In the most general sense, a business process may be thought of as multiple organizations interacting with each other to obtain their respective business goals. Supporting autonomy and compliance checking are key for business processes: each organization in a process is free to act as it pleases within the constraints of the contracts it enters into with others; violation of a contract typically means additional penalties.
Involvement of the supplementary eye field in oculomotor predictive behavior
Authors: Thomas Nyffeler, Sophie Rivaud-Pechoux, Nicolas Wattiez, Bertrand Gaymard
Venue: Journal of Cognitive Neuroscience (2008)

The presentation of saccadic and smooth pursuit eye movements as two separate systems has recently been reconsidered: The two subsystems share a number of anatomical structures, and recent data suggest that this sharing also extends to physiological processes. The aim of our study was first to test whether these two subsystems share a common predictive process. We designed a new predictive smooth pursuit paradigm that requires the triggering of unpredictable saccades, performed either during low (ongoing pursuit) or high (pursuit direction reversal) predictive behavior. Saccade latency was used as a probe to reveal a possible sharing of prediction between the two subsystems. The main finding was that saccade latencies were markedly decreased when triggered around pursuit direction reversal and performed in the direction of the predicted pursuit. The aim of the second part of this study was to determine the neural substrate of this common predictive process. According to previous studies, the supplementary eye field (SEF) would be involved in the control of predictive pursuit. The same subjects therefore performed the same tasks, and transcranial magnetic stimulation (TMS) was applied over this area: Decreased saccade latencies were no longer observed, whereas it continued to be observed when applied over the occipital cortex. These results are consistent with (1) The existence of a common predictive process shared by both oculomotor subsystems; (2) The view of the SEF not as a primary oculomotor area but as a higher order structure able to elaborate complex processes, such as prediction, independently of the oculomotor output.
Application of Network Smart Cards to Citizens Identification Systems
Authors: Joaquin Torres, Mildrey Carbonell, Jesus Tellez, Jose M. Sierra
Venue: Proceedings of the 8th IFIP WG 8.8/11.2 international conference on Smart Card Research and Advanced Applications (2008)

This paper proposes a new authentication and authorization architecture based on a network smart card with identification purposes: ID-NSCard. Thus, a citizen who holds this kind of device might be securely authenticated by a remote authoritative server in an identification system. This work shows how the standardized specifications are transparently reused and integrated in the proposed architecture. Details of the protocol and authentication mechanisms are provided for a Case of Study: Spanish National Electronic ID Card.
Examining the relationship between rural middle school laptop programs and familial online shopping
Authors: Michael Ewald
Venue:  (2008)

The purpose of this research was to examine the relationship between the assignment of laptops to public middle school students in remote, rural areas and the online shopping behavior of the parents of the students. The quantitative research study was conducted with the goal of an increased understanding of familial influences regarding the use of technology. The theoretical basis for the study was Everett Rogers' (1995) Innovation Diffusion Theory. A telephone survey was administered to randomly selected rural households in Maine and New Hampshire, states with and without publicly funded laptop programs, respectively. The analysis of the data supported, at the p=0.05 significance level, the hypothesis that there is no correlation between a rural child's participation in a school laptop program and previous online shopping of adult family members. The analysis supported the hypothesis of a correlation between a rural child's participation in a school laptop program and intent of adult family members to shop online within the next six months. Analysis of the data also suggested that there is a correlation between the amount of time a rural child spends using the Internet at home and the adult family member's intent to shop online. Furthermore, the data indicated a correlation between a child in a laptop program teaching an adult family member about the Internet and the adult's intent to shop online. The benefits of this research extend to educators, legislators, business managers, marketers and researchers. Educators could use the study because the data analysis revealed that parents are influenced by the child's level of interest in the technology. The study could be used by legislators when considering whether to extend and improve high-speed Internet access to rural areas. The data indicated that 54.3% of rural consumers intend to use online shopping in the future, which may provide entrepreneurs and marketers with a better understanding of this group of consumers. Also, this research could be of value to researchers investigating factors in outshopping in rural areas and the implications of sales tax revenues generated or lost from online shopping.
Pre-processing Optimisation Applied to the Classical Integer Programming Model for Statistical Disclosure Control
Authors: Martin Serpell, Alistair Clark, Jim Smith, Andrea Staggemeier
Venue: Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases (2008)

A pre-processing optimisation is proposed that can be applied to the integer and mixed integer linear programming models that are used to solve the cell suppression problem in statistical disclosure control. In this paper we report our initial findings which confirm that in many situations the pre-processing optimisation can considerably reduce the resources required by the solver hence allowing either statistical tables to be protected quicker, or larger statistical tables to be protected. This pre-processing optimisation may be suitable for application to the ¿-Argus Optimal Method used in protecting statistical tables.
Multi-layer survivable routing mechanism in GMPLS based optical networks
Authors: Xingwei Wang, Lei Guo, Fei Yang, Tengfei Wu, Wei Ji
Venue: Journal of Systems and Software (2008)

The structure of IP/MPLS over optical networks has become the trend for new generation backbone transport networks since the technology of general multi-protocol label switching (GMPLS) can realize the seamless converage between IP and optical networks. At the same time, due to the high-speed transmission rate of each wavelength in optical networks, survivability is a very important issue and has been studied all through these years. Therefore, in new generation GMPLS based networks, it is very necessary to investigate the multi-layer survivable algorithms. In this paper, we comprehensively review the existing survivable algorithms in multi-layer networks and analyze the shortages of current researches. Based on previous studies, we prospect challenges and propose new solutions of designing efficient survivable algorithms to well guide the future work of researchers in multi-layer networks.
Efficient non-myopic value-of-information computation for influence diagrams
Authors: Wenhui Liao, Qiang Ji
Venue: International Journal of Approximate Reasoning (2008)

In an influence diagram (ID), value-of-information (VOI) is defined as the difference between the maximum expected utilities with and without knowing the outcome of an uncertainty variable prior to making a decision. It is widely used as a sensitivity analysis technique to rate the usefulness of various information sources, and to decide whether pieces of evidence are worth acquisition before actually using them. However, due to the exponential time complexity of exactly computing VOI of multiple information sources, decision analysts and expert-system designers focus on the myopic VOI, which assumes observing only one information source, even though several information sources are available. In this paper, we present an approximate algorithm to compute non-myopic VOI efficiently by utilizing the central-limit theorem. The proposed method overcomes several limitations in the existing work. In addition, a partitioning procedure based on the d-separation concept is proposed to further improve the computational complexity of the proposed algorithm. Both the experiments with synthetic data and the experiments with real data from a real-world application demonstrate that the proposed algorithm can approximate the true non-myopic VOI well even with a small number of observations. The accuracy and efficiency of the algorithm makes it feasible in various applications where efficiently evaluating a large amount of information sources is necessary.
Feature Extraction of Seal Imprint Based on the Double-Density Dual-Tree DWT
Authors: Li Runwu, Fang Zhijun, Wang Shengqian, Yang Shouyuan
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

The most important problem on seal imprint verification is to extract the imprint feature, which is independent upon varying conditions. This paper proposes a new method to extract the feature of seal imprint using the double-density dual-tree DWT due to its good directional selectivity, approximate shift invariance and computational efficiency properties. 16 different directions information is obtained as a seal imprint image transforms by using double-density dual-tree DWT. Experimental results show that their directional behaviors are much different, although the frequency distributions of true seals are similar to false seals'. This method is stable and computationally efficient for seal imprint.
SVM-Based Text-Independent Speaker Verification Using Derivative Kernel in the Reference GMM Space
Authors: Minqiang Xu, Beiqiang Dai, Dongxing Xu, Shiqing Yang, Qingsong Liu
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

This paper proposes a new SVM-based method for text-independent speaker verification using derivative kernel in the reference Gaussian Mixture Model(GMM) space. The model for speaker utilizes the power of SVM and GMM, reference GMM used first, and then SVM followed. Using the reference GMM, not only clusters and compacts the speech, but also distinguishes the reference speaker and imposters. Then, derivative kernel combines SVM and GMM effectively. Experiments on text-independent speaker verification on NIST SRE 2001 dataset show that the Equal Error Rate(EER) of the new method is reduced to 6.51% from 9.88%.