ppxscal/embedding_network huggingface dataset:
Delaminated Real-Time Network Supporting Environment Based on RTX in Simulation
Authors: Tao You, Cheng-lie Du, Yi-an Zhu
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Simulation supporting environment is the important part of simulation system. Different level requests variously to real-time behavior in the complex real-time simulation system. Under the Environment of RTX and Windows-NT, Performance index of Ethernet and reflective memory network including data transmission delay and delay jitter was measured. The comparison of performance index between the environment of RTX and the environment of Windows-NT proves that the system under the environment of RTX has more real-time behavior and more reliability. Virtual shared memory middleware based on real time Ethernet and reflective memory network is also designed and implemented. According to the distributed simulation system of a weapon system, the design of delaminated real-time network framework was also provided.
Analysis of Breakdowns in Menu-Based Interaction Based on Information Scent Model
Authors: Yukio Horiguchi, Hiroaki Nakanishi, Tetsuo Sawaragi, Yuji Kuroda
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

High communicability of the menu-based system is on the basis of consistent vision and clear policy in designing the system of menus, and then they should be perceivable to the users. In this light, failures in menu-based interactions can be explained that they might emerge from lack of information in the users' available cues to identify the design vision. This study focuses on communicative breakdowns in menu-based human-computer interactions from this perspective, and investigates their causes in ill-organized structures of menu hierarchy in terms of the user's interpretation of the menu items. Pirolli's information scentmodel is extended and utilized as an analytical tool for describing the meaning system of menus from the users' point of view, and their decision making in search of particular menu items is analyzed by use of information scent.
Redefining Interoperability: Understanding Police Communication Task Environments
Authors: Gyu H. Kwon, Tonya L. Smith-Jackson, Charles W. Bostian
Venue: Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009 (2009)

The goal of this research is to understand the concept of police communication environments related to interoperable issues. Interoperability is critical to both inter- and intra- organizational communication. Especially in the emergency operations with multiple groups at the same place, the importance of interoperability has been much appreciated. This study used semi-structured interviews to examine the police communication issues and reconceptualize interoperability in the police communication domain. Based on the interview, we identified three important concepts to specify interoperable groups. First, highly distributed decision making processes are problematic for multiple communication needs. Second, a police team is self-organized at the scene. Finally, their operational boundaries are tentative based on contextual information. Based on these main concepts, we provided high-level suggestions to design a police communication system based on cognitive radio technology.
A New Algorithm for Digital Audio Watermarking Based on DWT
Authors: Meng Lihua, Yang Shuangyuan, Jiang Qingshan
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

Internet wide spreads in our daily life, copyright protection of audio frequency becomes to a hotspot. In this paper, a novel algorithm for digital audio watermarking based on the discrete wavelet transform is proposed. In the condition of quantization, the watermark was embedded and extracted based on the contextual border upon low-frequency coefficients which was sorted. The experimental results show that this algorithm has good imperceptibility and robustness against common attack, and the watermark can be extracted without original data.
Head Pose Estimation from Passive Stereo Images
Authors: M. D. Breitenstein, J. Jensen, C. Høilund, T. B. Moeslund, L. Gool
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

We present an algorithm to estimate the 3D pose (location and orientation) of a previously unseen face from low-quality range images. The algorithm generates many pose candidates from a signature to find the nose tip based on local shape, and then evaluates each candidate by computing an error function. Our algorithm incorporates 2D and 3D cues to make the system robust to low-quality range images acquired by passive stereo systems. It handles large pose variations (of ±90 ° yaw and ±45 ° pitch rotation) and facial variations due to expressions or accessories. For a maximally allowed error of 30°, the system achieves an accuracy of 83.6%.
KSC-PaL: a peer learning agent that encourages students to take the initiative
Authors: Cynthia Kersey, Barbara Di Eugenio, Pamela Jordan, Sandra Katz
Venue: Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications (2009)

We present an innovative application of discourse processing concepts to educational technology. In our corpus analysis of peer learning dialogues, we found that initiative and initiative shifts are indicative of learning, and of learning-conducive episodes. We are incorporating this finding in KSC-PaL, the peer learning agent we have been developing. KSC-PaL will promote learning by encouraging shifts in task initiative.
Genetic hybrid tuning of VARMAX and state space algorithms
Authors: Ralf &#x00d6;stermark
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2009)

The aim of the study was to monitor the system theoretic exogenous variables augmented state space algorithm of Aoki (State space modelling of time series. Springer, Heidelberg, 1987) and the VARMAX algorithm of Spliid (J Am Stat Assoc 78(384):843&#x2013;849, 1983) within a geno-mathematical framework towards optimal parametric conditions/search intervals. Both algorithms were implemented as an integrated support library for a general computational platform, the Genetic Hybrid Algorithm (GHA), where some key parameters of the algorithms are defined in a search process utilizing a mixed geno-mathematical search technique. The empirical results of our tests using real economic data from the European stock market are encouraging. Specifically, the information criteria used in the VARMAX-search (Vector Autoregressive Moving Average algorithm with Exogenous variables) algorithm tend to favor parsimonious model representations automatically. Furthermore, the state space algorithm captures almost the same dynamics as the complex VARMAX-model estimated in the study. Both algorithms have encouraging in sample properties. When generating k-steps forecasts out-of-sample, k&#x00a0;>&#x00a0;1, the state space algorithm seems to deteriorate faster than the VARMAX algorithm, however. The results suggest that more empirical testing is needed, especially in different situations with different degrees of model order and stationarity conditions, in order to provide more evidence on the suitability of the competing methods in particular cases. We demonstrated that the Genetic Hybrid Algorithm can be used as a generic platform for parametric search in vector valued time series modelling. Efficient procedures for optimal grouping of the individual time series processes and recognition of heteroskedasticity may improve the performance of the algorithms further.
Graph-Based Registration of Partial Images of City Maps Using Geometric Hashing
Authors: Steffen Wachenfeld, Klaus Broelemann, Xiaoyi Jiang, Antonio Krüger
Venue: Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition (2009)

In this paper, we present a novel graph-based approach for the registration of city maps. The goal is to find the best registration between a given image, which shows a small part of a city map, and stored map data. Such registration is important in fields like mobile computing for augmentation purposes. Until now, RFID tags, markers, or regular dot grids on specially prepared maps are typically required. In this paper we propose a graph-based method to avoid the need of special maps. It creates a graph representation of a given input image and robustly finds an optimal registration using a geometric hashing technique. Our approach is translation, scale and rotation invariant, map type independent and robust against noise and missing data.
Indifferentiability of Permutation-Based Compression Functions and Tree-Based Modes of Operation, with Applications to MD6
Authors: Yevgeniy Dodis, Leonid Reyzin, Ronald L. Rivest, Emily Shen
Venue: Fast Software Encryption: 16th International Workshop, FSE 2009 Leuven, Belgium, February 22-25, 2009 Revised Selected Papers (2009)

MD6 [17] is one of the earliest announced SHA-3 candidates, presented by Rivest at CRYPTO'08 [16]. Since then, MD6 has received a fair share of attention and has resisted several initial cryptanalytic attempts [1,11].Given the interest in MD6, it is important to formally verify the soundness of its design from a theoretical standpoint. In this paper, we do so in two ways: once for the MD6 compression function and once for the MD6 mode of operation. Both proofs are based on the indifferentiability framework of Maurer et al. [13](also see [9]).The first proof demonstrates that the "prepend/map/chop" manner in which the MD6 compression function is constructed yields a compression function that is indifferentiable from a fixed-input-length (FIL), fixed-output-length random oracle.The second proof demonstrates that the tree-based manner in which the MD6 mode of operation is defined yields a hash function that is indifferentiable from a variable-input-length (VIL), fixed-output-length random oracle.Both proofs are rather general and apply not only to MD6 but also to other sufficiently similar hash functions.These results may be interpreted as saying that the MD6 design has no structural flaws that make its input/output behavior clearly distinguishable from that of a VIL random oracle, even for an adversary who has access to inner components of the hash function. It follows that, under plausible assumptions about those inner components, the MD6 hash function may be safely plugged into any application proven secure assuming a monolithic VIL random oracle.
Experiencing Rare and Unusual Events Richly: The Role of Middle Managers in Animating and Guiding Organizational Interpretation
Authors: Tammy E. Beck, Donde Ashmos Plowman
Venue: Organization Science (2009)

Organizations have difficulty learning from rare and unusual events because of their inability to interpret these events. Because organizations develop habitual ways of interpreting events---often top down---they can easily miss the novelty of rare and unusual events, which prevents them from experiencing events “richly.” We propose a multilevel, multistaged model of organizational interpretation that highlights the important, but generally unacknowledged, role middle managers can play in helping organizations experience rare and unusual events richly. Our model accounts for the effect of cognitive biases and hierarchical context on organizational interpretation. Because of their proximity to the interpretations of both strategic and front-line managers, middle managers can encourage divergence in interpretations of managers across hierarchical levels during early stages of the interpretation process and can blend and synthesize the divergent interpretations of managers during later stages. In this way middle managers contribute to a dynamic process of organizational interpretation in which multiple filters from throughout the organization help frame and enrich interpretations of rare and unusual events, which enables organizational learning.
Incremental construction of minimal acyclic finite state automata and transducers
Authors: Jan Daciuk, Bruce W. Watson, Richard E. Watson
Venue: Proceedings of the International Workshop on Finite State Methods in Natural Language Processing (1998)

In this paper, we describe a new method for constructing minimal, deterministic, acyclic finite state automata and transducers. Traditional methods consist of two steps. The first one is to construct a trie, the second one --- to perform minimization. Our approach is to construct an automaton in a single step by adding new strings one by one and minimizing the resulting automaton on-the-fly. We present a general algorithm as well as a specialization that relies upon the lexicographical sorting of the input strings.
The effects of corrected-errors in asynchronous video based lessons on task efficiency
Authors: Antonios Saravanos, Seungoh Paek, Jin Kuwata, Alexandra Saravanos
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

This study explores the impact that student exposure to instructor made corrected-errors can have on their pedagogy through the use of asynchronous video-based lessons. We define corrected-errors as segments in the lesson where the instructor makes an error, identifies that an error has been made, and then goes on to correct it. Our study measures the learners' performance on a similar task by looking at the efficiency in which that task is carried out. We hypothesize that the modeling of error detection and correction skills when coupled with the instructor's explicit meta-cognitive explanation and reflection of errors, will lead to an increase in efficiency.
Pairwise Similarity Propagation Based Graph Clustering for Scalable Object Indexing and Retrieval
Authors: Shengping Xia, Edwin R. Hancock
Venue: Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition (2009)

Given a query image of an object of interest, our objective is to retrieve all instances of that object with high precision from a database of scalable size. As distinct from the bag-of-feature based methods, we do not regard descriptor quantizations as "visual words". Instead a group of selected SIFT features of an object together with their spatial arrangement are represented by an attributed graph. Each graph is then regarded as a "visual word". We measure the similarity between graphs using the similarity of SIFT features and the compatibility of their arrangement. Using the similarity measure we efficiently identify the set of K nearest neighbor graphs (KNNG) using a SOM based clustering tree. We then extend the concept of "query expansion" widely used in text retrieval to develop a graph clustering method based on pairwise similarity propagation (SPGC), in that the trained KNNG information is utilized for speeding up. Using SOM based clustering tree and SPGC, we develop a framework for scalable object indexing and retrieval. We illustrate these ideas on a database of over 50K images spanning more than 500 objects. We show that the precision is substantially boosted, achieving total recall in many cases.
Calibration of options on a reduced basis
Authors: Olivier Pironneau
Venue: Journal of Computational and Applied Mathematics (2009)

Calibration of models is an important step in financial engineering. However it can be costly, especially in view of the increasing complexity of the models. In this paper we explore the use of reduced basis as is done in fluid mechanics for the Navier-Stokes equations or as proposed by Maday, Patera and Turinici [Y. Maday et al., A priori convergence theory for reduced-basis approximations of single-parameter elliptic partial differential equations, J. Sci. Comput. 17 (1-4) (2002) 437-446]. It is shown that the method works well if we use convex combination of the basis functions instead of the more general linear combination; however, while this idea makes sense in view of the properties of the Black-Scholes equation, we have no proof to general linear combination; however, while this idea makes sense in view of the properties of the Black-Scholes equation, we have no proof to justify it mathematically. The paper presents a numerical investigation of the problem posed.
Enhanced speech features by single-channel joint compensation of noise and reverberation
Authors: Matthias Wölfel
Venue: IEEE Transactions on Audio, Speech, and Language Processing (2009)

For a natural verbal communication between humans and machines, automatic speech recognition, which works reasonably well on recordings captured with mid- or far-field microphones, is essential. While a lot of research and development are devoted to address one of the two distortions frequently encountered in mid- and far-field sound pickup, namely noise or reverberation, less effort has been undertaken to jointly combat both kinds of distortions. In our view, however, this is essential to further reduce the demolishing effect by moving the microphone away from the speaker's mouth because in real environments both kinds of distortions are present. In this paper, we propose a first step into this direction by integrating an estimate of the reverberation energy derived by an auxiliary model based on multistep linear prediction, into a framework, which, so far tracks and removes nonstationary additive distortion by particle filters in a low-dimension logarithmic power frequency domain. On actual recordings with different speaker-to-microphone distances, we observe that combating, in the feature space, either nonstationary noise or reverberation alone, on a single channel, is already able to improve speech recognition performance before and after acoustic model adaptation. Furthermore, we observe that a simple concatenation of techniques addressing either additive noise or reverberation can further improve the accuracy in some cases. Last but not least, we demonstrate that the joint estimation and removal of both kinds of distortions, as proposed in this publication, further improve the accuracy of the text output.
Detection of Duplicated Regions in Tampered Digital Images by Bit-Plane Analysis
Authors: Edoardo Ardizzone, Giuseppe Mazzola
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

In this paper we present a new method for searching duplicated areas in a digital image. The goal is to detect if an image has been tampered by a copy-move process. Our method works within a convenient domain. The image to be analyzed is decomposed in its bit-plane representation. Then, for each bit-plane, block of bits are encoded with an ASCII code, and a sequence of strings is analyzed rather than the original bit-plane. The sequence is lexicographically sorted and similar groups of bits are extracted as candidate areas, and passed to the following plane to be processed. Output of the last planes indicates if, and where, the image is altered.
Fusing Time-of-Flight Depth and Color for Real-Time Segmentation and Tracking
Authors: Amit Bleiweiss, Michael Werman
Venue: Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging (2009)

We present an improved framework for real-time segmentation and tracking by fusing depth and RGB color data. We are able to solve common problems seen in tracking and segmentation of RGB images, such as occlusions, fast motion, and objects of similar color. Our proposed real-time mean shift based algorithm outperforms the current state of the art and is significantly better in difficult scenarios.
Mining uncertain data for constrained frequent sets
Authors: Carson Kai-Sang Leung, Dale A. Brajczuk
Venue: Proceedings of the 2009 International Database Engineering & Applications Symposium (2009)

Data mining aims to search for implicit, previously unknown, and potentially useful pieces of information---such as sets of items that are frequently co-occurring together---that are embedded in data. The mined frequent sets can be used in the discovery of correlation or casual relations, analysis of sequences, and formation of association rules. Since its introduction, frequent set mining has been the subject of numerous studies. Most of these studies find all the frequent sets from transaction databases of precise data, in which items within each transaction are definitely known and precise. However, there are many real-life situations in which the user is interested in only some tiny portions of the entire frequent sets, and there are also many situations in which data in the transaction databases are uncertain. This calls for both (i) constrained frequent set mining (which finds frequent sets that satisfy user constraints indicating the user interest) and (ii) frequent set mining from uncertain data. In this paper, we propose a tree-based system that integrates these two kinds of frequent set mining. The resulting mining system avoids candidate generation; it pushes the user constraints inside the mining process, which avoids unnecessary computation. Consequently, the system effectively mines from transaction databases of uncertain data for only those frequent sets satisfying the user-specified constraints.
Systematic Exploration of Efficient Query Plans for Automated Database Restructuring
Authors: Maxim Kormilitsin, Rada Chirkova, Yahya Fathi, Matthias Stallmann
Venue: Proceedings of the 13th East European Conference on Advances in Databases and Information Systems (2009)

We consider the problem of selecting views and indexes that minimize the evaluation costs of the important queries under an upper bound on the disk space available for storing the views/indexes selected to be materialized. We propose a novel end-to-end approach that focuses on systematic exploration of plans for evaluating the queries. Specifically, we propose a framework (architecture) and algorithms that enable selection of views/indexes that contribute to the most efficient plans for the input queries, subject to the space bound. We present strong optimality guarantees on our architecture. Our algorithms search for sets of competitive plans for queries expressed in the language of conjunctive queries with arithmetic comparisons. This language captures the full expressive power of SQL select-project-join queries, which are common in practical database systems. Our experimental results demonstrate the competitiveness and scalability of our approach.
Segment predictability as a cue in word segmentation: application to modern Greek
Authors: C. Anton Rytting
Venue: Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology (2004)

Several computational simulations of how children solve the word segmentation problem have been proposed, but most have been applied only to a limited number of languages. One model with some experimental support uses distributional statistics of sound sequence predictability (Saffran et al. 1996). However, the experimental design does not fully specify how predictability is best measured or modeled in a simulation. Saffran et al. (1996) assume transitional probability, but Brent (1999a) claims mutual information (MI) is more appropriate. Both assume predictability is measured locally, relative to neighboring segment-pairs. This paper replicates Brent's (1999a) mutual-information model on a corpus of childdirected speech in Modern Greek, and introduces a variant model using a global threshold. Brent's finding regarding the superiority of MI is confirmed; the relative performance of local comparisons and global thresholds depends on the evaluation metric.