ppxscal/embedding_network huggingface dataset:
Abstract Geometrical Computation and Computable Analysis
Authors: Jérôme Durand-Lose
Venue: Proceedings of the 8th International Conference on Unconventional Computation (2009)

Extended Signal machines are proven able to compute any computable function in the understanding of recursive/computable analysis (CA), here type-2 Turing machines (T2-TM) with signed binary encoding. This relies on an intermediate representation of any real number as an integer (in signed binary) plus an exact value in ( ¿ 1,1) which allows to have only finitely many signals present outside of the computation. Extracting a (signed) bit, improving the precision by one bit and iterating the T2-TM only involve standard signal machines.For exact CA-computations, T2-TM have to deal with an infinite entry and to run through infinitely many iterations to produce an infinite output. This infinite duration can be provided by constructions emulating the black hole model of computation on an extended signal machine. Extracting/encoding an infinite sequence of bits is achieved as the limit of the approximation process with a careful handling of accumulations and singularities.
Compact modeling of a PD SOI MESFET for wide temperature designs
Authors: A. Balijepalli, J. Ervin, W. Lepkowski, Y. Cao, T. J. Thornton
Venue: Microelectronics Journal (2009)

A compact model for the partially depleted (PD) silicon-on-insulator (SOI) metal semiconductor field effect transistor (MESFET) is presented. The absence of a gate-oxide makes the SOI MESFET extremely robust, able to withstand high voltages, and useful for extreme environment electronics. These devices have been fabricated using a standard SOI CMOS process. In contrast to SOI MOSFETs and GaAs MESFETs, the source-substrate voltage has a significant impact on the channel current. In this work a model has been developed that includes the effect of the buried oxide on the performance of the MESFET. The model has been verified for a wide temperature range of -180 to 150^oC. A behavioral model has been included to model the breakdown voltage. The core DC and RF models have been adapted from the commercially available Triquint's Own Model (TOM3) MESFET model. Building from the TOM3 model, a measurement-based approach is used to develop a four-terminal compact model using Verilog-A. The charge-based approach, using S-parameter measurements was used to develop the capacitance model. We also present a voltage reference circuit using two MESFET transistors to verify the model and explore wide temperature range circuit applications.
Learning to evaluate scientific models
Authors: William J. Pluta, Luke A. Buckland, Clark A. Chinn, Ravit Golan Duncan, Richard A. Duschl
Venue: Proceedings of the 8th international conference on International conference for the learning sciences - Volume 3 (2008)

The construction and evaluation of scientific models, together with the iterative modification of these models in response to evidence, constitute paradigmatic scientific practices. If inquiry instruction is to engage students in authentic scientific reasoning, these practices need to become routine in the science curriculum. This paper reports on some of the difficulties middle-school students experience in a learning environment focused on model-and evidence-based reasoning and suggests a promising scaffold to address these difficulties.
Written Texts as Statistical Mechanical Problem
Authors: Kostadin Koroutchev, Elka Korutcheva, Jian Shen
Venue: Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory (2009)

In this article we present a model of human written text based on statistical mechanics consideration. The empirical derivation of the potential energy for the parts of the text and the calculation of the thermodynamic parameters of the system, show that the "specific heat" corresponds to the semantic classification of the words in the text, separating keywords, function words and common words. This can give advantages when the model is used in text searching mechanisms.
Structural, transitive and latent models for biographic fact extraction
Authors: Nikesh Garera, David Yarowsky
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

This paper presents six novel approaches to biographic fact extraction that model structural, transitive and latent properties of biographical data. The ensemble of these proposed models substantially outperforms standard pattern-based biographic fact extraction methods and performance is further improved by modeling inter-attribute correlations and distributions over functions of attributes, achieving an average extraction accuracy of 80% over seven types of biographic attributes.
New Cryptanalysis of Block Ciphers with Low Algebraic Degree
Authors: Bing Sun, Longjiang Qu, Chao Li
Venue: Fast Software Encryption: 16th International Workshop, FSE 2009 Leuven, Belgium, February 22-25, 2009 Revised Selected Papers (2009)

Improved interpolation attack and new integral attack are proposed in this paper, and they can be applied to block ciphers using round functions with low algebraic degree. In the new attacks, we can determine not only the degree of the polynomial, but also coefficients of some special terms. Thus instead of guessing the round keys one by one, we can get the round keys by solving some algebraic equations over finite field. The new methods are applied to $\mathcal{PURE}$ block cipher successfully. The improved interpolation attacks can recover the first round key of 8-round $\mathcal{PURE}$ in less than a second; r-round $\mathcal{PURE}$ with r ≤ 21 is breakable with about 3 r ¿ 2 chosen plaintexts and the time complexity is 3 r ¿ 2 encryptions; 22-round $\mathcal{PURE}$ is breakable with both data and time complexities being about 3×320. The new integral attacks can break $\mathcal{PURE}$ with rounds up to 21 with 232 encryptions and 22-round with 3×232 encryptions. This means that $\mathcal{PURE}$ with up to 22 rounds is breakable on a personal computer.
Multilevel Analysis of Human Performance Models in Safety-Critical Systems
Authors: Jeronimo Dzaack, Leon Urbas
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

Safety-critical systems are technical systems whose failure may cause injury or death to human beings. Tools used in the design and evaluation of safety-critical systems are redundancy and formal methods to ensure a proper operating behavior. To integrate human factors into the engineering-process of safety-critical systems it is necessary to take into account cognitive aspects of human beings while interacting with these systems. Formal human performance models can be applied to support the design and evaluation. These cognitive models interact with the technical system and provide a wide range of objective data (e.g., execution times). But using human performance models requires validating their behavior and internal structure in advance. Especially in the context of safety-critical systems this is an important issue. In this contribution the possibilities of multilevel analysis of human performance models are shown and discussed. Selected tools are introduced and related to a derived taxonomy of multilevel analysis.
Graded information extraction by neural-network dynamics with multihysteretic neurons
Authors: Yukihiro Tsuboshita, Hiroshi Okamoto
Venue: Neural Networks (2009)

A major goal in the study of neural networks is to create novel information-processing algorithms inferred from the real brain. Recent neurophysiological evidence of graded persistent activity suggests that the brain possesses neural mechanisms for retrieval of graded information, which could be described by the neural-network dynamics with attractors that are continuously dependent on the initial state. Theoretical studies have also demonstrated that model neurons with a multihysteretic response property can generate robust continuous attractors. Inspired by these lines of evidence, we proposed an algorithm given by the multihysteretic neuron-network dynamics, devised to retrieve graded information specific to a given topic (i.e., context, represented by the initial state). To demonstrate the validity of the proposed algorithm, we examined keyword extraction from documents, which is best fitted for evaluating the appropriateness of retrieval of graded information. The performance of keyword extraction by using our algorithm was significantly high (measured by the average precision of document retrieval, for which the appropriateness of keyword extraction is crucial) compared with standard document-retrieval methods. Moreover, our algorithm exhibited much higher performance than the neural-network dynamics with bistable neurons, which can also produce robust continuous attractors but only represent dichotomous information at the single-cell level. These findings indicate that the capability to manage graded information at the single-cell level was essential for obtaining a high performing algorithm.
Non-stationary policy learning in 2-player zero sum games
Authors: Steven Jensen, Daniel Boley, Maria Gini, Paul Schrater
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

A key challenge in multiagent environments is the construction of agents that are able to learn while acting in the presence of other agents that are simultaneously learning and adapting. These domains require on-line learning methods without the benefit of repeated training examples, as well as the ability to adapt to the evolving behavior of other agents in the environment. The difficulty is further exacerbated when the agents are in an adversarial relationship, demanding that a robust (i.e. winning) non-stationary policy be rapidly learned and adapted. We propose an on-line sequence learning algorithm, ELPH, based on a straightforward entropy pruning technique that is able to rapidly learn and adapt to non-stationary policies. We demonstrate the performance of this method in a non-stationary learning environment of adversarial zero-sum matrix games.
OI and fMRI Signal Separation by Maximizing Both Temporal and Spatial Structures
Authors: Ming Li, Yadong Liu, Dewen Hu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

A novel signal source separation method is introduced for analysis of intrinsic Optical Imaging (OI) and functional Magnetic Resonance Imaging (fMRI) data. This method is based on the fact that all real interesting signals are autocorrelated spatially as well as temporally. Many signal source separation algorithms which using autocorrelation or other structure information of the interesting signals, e.g. Canonical Correlation Analysis (CCA), have been proposed before. However, these traditional methods using only temporal structure in temporal signal separation and only spatial structure in spatial signal separation. In this article, we have given a new definition of the spatial distribution pattern of temporal signals, this make it possible to represent the spatial autocorrelations of temporal sources. Then an objective function which takes account of both temporal and spatial autocorrelations could be constructed. By maximizing such objective function, it is expected to find the real signal sources underlie the mixed data. The comparison experiment shows that the new method is of better performance in recovering the signal sources than the traditional methods.
A Usability Evaluation Method Applying AHP and Treemap Techniques
Authors: Toshiyuki Asahi, Teruya Ikegami, Shin'Ichi Fukuzumi
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

This report proposes a visualization technique for checklist-based usability quantification methods. By applying the Treemap method, the hierarchical structure of checklists, weights of check items and evaluation results for target systems can be viewed at a glance. Effective support for usability analysis and its presentation tasks of usability evaluation results are expected. A prototype tool was implemented on a PC and experimental studies assuming actual usability evaluation tasks were conducted. The results indicate that the proposed method improves performance time of some typical tasks. Usability engineers gave higher subjective scores on the usefulness of the proposed method than that of printed table presentation.
Analysis and Study on Temperature Mathematical Model and Temperature Field in Milling Processing
Authors: X. L. Sui, L. J. Jin, J. T. Zhang, X. P. Yang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

According to theory of metal cutting and heat transfer, mathematical model of temperature field when work piece is milled by ball-milling cutter was established using moving heat source theory. Joint modeling method of work piece temperature field was studied in the environment of PRO / E and ALGOR. Three dimensional modeling of work piece was finished by PRO/E, and all-moving surface heat source's temperature field in milling process were dynamically simulated and had finite element analysis using ALGOR, and then distributed characteristic of the temperature field and rule that temperature on each point changed with time were got. This technology has laid a foundation for research of milling temperature's dynamic simulation and milling thermal deformation.
IBM Virtualization Engine Ts7740 R1.5 and Ts7720: New Virtualization Options for Mainframe Servers
Venue:  (2009)

The IBM Virtualization Engine TS7700 provides tape virtualization for the IBM System z environment. The Virtualization Engine TS7700 is designed to provide improved performance and capacity to help lower the total cost of ownership for tape processing. It introduces a new modular, scalable, high-performing architecture for mainframe tape virtualization. The TS7700 is available as the TS7740 R1.5, which brings significant enhancements over its previous release and now also comes as a disk-only solution, the TS7720, that does not require physical tape attachment. The Virtualization Engine TS7700 integrates the advanced performance, capacity, and data integrity design of the 3592 Tape Drives, the IBM industry-leading tape technology, with high-performance disk and a new advanced IBM System p server to form a storage hierarchy managed by robust storage management firmware with extensive self management capability. It includes functions such as advanced policy management to control physical volume pooling, cache management, dual copy, dual copy across a grid network, and copy mode control. The TS7700 offers enhanced statistical reporting and a single, standards-based management interface for TS7700 management. In addition to providing a detailed description of the Virtualization Engine TS7700 models, this book discusses the tasks involved with planning, implementing, and operating the Virtualization Engine TS7700, as well as describing migration considerations. This IBM Redbooks publication covers the Virtualization Engine TS7740 Release 1.5 and the Virtualization Engine TS7720 and includes information about supported tape drives and libraries current at the time of writing. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Formal Specification and Automatic Analysis of Business Processes under Authorization Constraints: An Action-Based Approach
Authors: Alessandro Armando, Enrico Giunchiglia, Serena Elisa Ponta
Venue: Proceedings of the 6th International Conference on Trust, Privacy and Security in Digital Business (2009)

We present an approach to the formal specification and automatic analysis of business processes under authorization constraints based on the action language $\cal{C}$. The use of $\cal{C}$ allows for a natural and concise modeling of the business process and the associated security policy and for the automatic analysis of the resulting specification by using the Causal Calculator (CCALC). Our approach improves upon previous work by greatly simplifying the specification step while retaining the ability to perform a fully automatic analysis. To illustrate the effectiveness of the approach we describe its application to a version of a business process taken from the banking domain and use CCALC to determine resource allocation plans complying with the security policy.
A finite-state morphological grammar of Hebrew
Authors: Shlomo Yona, Shuly Wintner
Venue: Proceedings of the ACL Workshop on Computational Approaches to Semitic Languages (2005)

Morphological analysis is a crucial component of several natural language processing tasks, especially for languages with a highly productive morphology, where stipulating a full lexicon of surface forms is not feasible. We describe HAMSAH (HAifa Morphological System for Analyzing Hebrew), a morphological processor for Modern Hebrew, based on finite-state linguistically motivated rules and a broad coverage lexicon. The set of rules comprehensively covers the morphological, morpho-phonological and orthographic phenomena that are observable in contemporary Hebrew texts. Reliance on finite-state technology facilitates the construction of a highly efficient, completely bidirectional system for analysis and generation. HAMSAH is currently the broadest-coverage and most accurate freely-available system for Hebrew.
A Content Analysis of Interviews with Players of Massively Multiplayer Online Role-Play Games (MMORPGs): Motivating Factors and the Impact on Relationships
Authors: Jacqui Taylor, James Taylor
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

This paper explores the intrapersonal and interpersonal motivations involved in the playing of MMORPGs, and the impacts of gaming on online and offline relationships. Twenty-one participants completed an online synchronous interview in which they discussed their personal experiences of playing MMORPGs. An online survey was then developed to further explore the findings of the interviews and this was completed by 52 participants. A content-analysis of the interview transcripts showed that interpersonal factors (such as social communication and group cohesion) were the strongest motivators for game-playing, supporting previous research [1]. The interview data also showed that there tended to be conflict, rather than integration, between online and offline relationships, however the questionnaire data showed the opposite. This was a small-scale pilot study and a further larger study is planned which will investigate whether Social Identity Theory can be used to explain players' perceptions of group and personal identity.
Web User Modeling via Negotiating Information Foraging Agent
Authors: Xuehong Tao, Yin-Leng Theng, Terence Ting
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

Information foraging theory lays a good foundation for web user modeling. However, the existing user modeling methods mainly focus on fixed information needs. In the real world, a user's information goal often evolves, and information foraging is a negotiation process between the user and the system. In this paper, we proposed an agent based approach that modeled the dynamic information seeking process of information foragers.
Monte Carlo Localization of Mobile Robot with Modified SIFT
Authors: Yu-quan Wang, Gui-hua Xia, Qi-dan Zhu, Guo-liang Zhao
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

The Scale Invariant Feature Transform, SIFT, is invariant to image translation, scaling, rotation, and is partially invariant to illumination changes. But, the time of features extraction and matching is huge, and the number of features is much larger then that is needed. To reduce the number of features generated by SIFT as well as their extraction and matching time，a modified approach based sampling is proposed. Mean-Shift algorithm is used in this modified SIFT to search local extrema points actively in scale space to improve the efficiency. The modified SIFT is used in Monte Carlo localization of mobile robots with omnidirectional sensor, it is demonstrated that the features extracted by modified SIFT are uniformly distributed in space, the time of feature extraction and matching is reduced obviously, and the mobile robots can localize itself accurately with a lower number of features.
Working Memory Differences in E-Learning Environments: Optimization of Learners' Performance through Personalization
Authors: Nikos Tsianos, Panagiotis Germanakos, Zacharias Lekkas, Costas Mourlas, George Samaras, Mario Belk
Venue: Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH (2009)

Working memory (WM) is a psychological construct that has a major effect on information processing, thus signifying its importance when considering individual differences and adaptive educational hypermedia. Previous work of the authors in the field has demonstrated that personalization on human factors, including the WM sub-component of visuospatial sketchpad, may assist learners in optimizing their performance. To that end, a deeper approach in WM has been carried out, both in terms of more accurate measurements and more elaborated adaptation techniques. This paper presents results from a sample of 80 university students, underpinning the importance of WM in the context of an e-learning application in a statistically robust way. In short, learners that have low WM span expectedly perform worse than learners with higher levels of WM span; however, through proper personalization techniques this difference is completely alleviated, leveling the performance of low and normal WM span learners.
Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach
Authors: Aliaksei Kerhet, Cormac Small, Harvey Quon, Terence Riauka, Russell Greiner, Alexander Mcewan, Wilson Roa
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scans in order to provide a radiation therapist with a "second reader" opinion about the tumour location. For each PET slice, our system extracts a set of attributes, passes them to a trained Support Vector Machine (SVM), and returns the optimal threshold value for distinguishing tumour from healthy voxels in that particular slice. We use this technique to analyse four different PET/CT 3D studies. The system produced fairly accurate segmentation, with Jaccard and Dice's similarity coefficients between 0.82 and 0.98 (the areas outlined by the returned thresholds vs. the ones outlined by the reference thresholds). Besides the high level of geometric similarity, a significant correlation between the returned and the reference thresholds also indicates that during the training phase, the learning algorithm effectively acquired the dependency between the extracted attributes and optimal thresholds.