ppxscal/embedding_network huggingface dataset:
Proceedings of the Workshop on Enhancing and Using Electronic Dictionaries
Venue: ACL Workshops (2004)

A dictionary is a vital component of any natural language processing system. While the digital form has a potential which has only been partially explored, seizing the new possibilities requires some rethinking. This is the goal of this one-day workshop. Creating, maintaining and exploiting intelligently a dictionary involves many skills, some of which we still lack full understanding of.
Part of speech tagging for Amharic using conditional random fields
Authors: Sisay Fissaha Adafre
Venue: Proceedings of the ACL Workshop on Computational Approaches to Semitic Languages (2005)

We applied Conditional Random Fields (CRFs) to the tasks of Amharic word segmentation and POS tagging using a small annotated corpus of 1000 words. Given the size of the data and the large number of unknown words in the test corpus (80%), an accuracy of 84% for Amharic word segmentation and 74% for POS tagging is encouraging, indicating the applicability of CRFs for a morphologically complex language like Amharic.
CISSP Cert Flash Cards Online, Retail Packaged Version, 1st edition
Authors: Shon Harris
Venue:  (2009)

CISSP Cert Flash Cards Online Shon Harris The CISSP Cert Flash Cards Online provides a concise review of all ten domains on the (ISC)2 CISSP exam. This online exam preparation tool consists of a custom flash card application loaded with 300 total questions that test your skills and enhance retention of exam topics. Questions are organized by exam objective, allowing you to focus your study on selected topics. You can choose to view cards in order or at random, and you can create custom sets from the entire bank of cards. The engine provides you with the ability to mark each question correct or incorrect and provides a detailed score report by category at the end of the exam. You can even write notes on each question and then get a printable PDF of all your notes aligned to the relevant questions. These robust features make this a truly unique learning tool: . Test your knowledge by entering your own answers . Grade your answers against the correct answer . Create custom question sets . View detailed score reports . Enter and print notes for each question . Use on any device that has a web browser and Internet connection CISSP Cert Flash Cards Online is an Internet-based service, available in both desktop and mobile device formats, allowing you to test yourself at home, at work, or on the go. See a demo and try it free at certflashcardsonline.com. System Requirements: Web browser and Internet connection US: $24.99 / CAN: $29.99 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
A methodology for short-term electric load forecasting based on specialized recursive digital filters
Authors: C. A. Maia, M. M. Gonçalves
Venue: Computers and Industrial Engineering (2009)

In this paper we propose a methodology for short-term electric load forecasting, which is adaptive and based on signal processing theory. The main interest here is to construct a next day predictor for the peak and hourly load. To this end the load data are organized into profiles according to day type and temperature interval. For each load profile, we use a specialized adaptive recursive digital filter, for which parameters are estimated on-line by using a recursive algorithm. As a result, the complete forecasting system is nonlinear and the prediction is computed based on the type and on the temperature interval of the next day. The effectiveness of the proposed methodology is illustrated by a numerical example, in which we compare performance of the proposed approach to a non-specialized and a naive predictors, by using the Mean Absolute Percentage Error (MAPE) of the forecasting errors.
Combination of Geometrical and Statistical Methods for Visual Navigation of Autonomous Robots
Authors: Naoya Ohnishi, Atsushi Imiya
Venue: Statistical and Geometrical Approaches to Visual Motion Analysis: International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008. Revised Papers (2009)

For visual navigation of an autonomous robot, detection of collision-free direction from an image/ image sequence captured by imaging systems mounted on the robot is a fundamental task. This collision free direction provides the next view to direct attention for computing the next collision free direction. Therefore, the robot requires a cyclic mechanism directing attention to the view and computing the collision free direction from that view. We combine a geometric method for free space detection and a statistical method for visual navigation of the mobile robot. Firstly, we deal with a random-sampling-based method for the detection of free space. Secondly, we deal with a statistical method for the computation of the collision avoiding direction. The robot finds free space using the visual potential defined from a series of views captured by a monocular camera system mounted on the robot to observe the view in front of the robot, We examine the statistical property of the gradient field of the visual potential. We show that the principal component of the gradient of the visual potential field yields the attention direction of the mobile robot for collision avoidance. Some experimental results of navigating the mobile robot in synthetic and real environments are presented.
Application of Unbalanced Data Approach to Network Intrusion Detection
Authors: Zhao Yueai, Chen Junjie
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In view of the current problems of HNIDS (high-speed network intrusion detection system), such as high packet loss rate, slow pace of testing for attacks and unbalanced data for detection. This paper presents a novel approach for HNIDS by taking two-stage strategy with load balancing model, In the on-line phase, the system captures the packets from network and split into small according the type of protocol, then detected intrusion though each sensor. In the off-line, training dataset are used to build model, which can detected intrusion. We discuss different approaches to unbalanced data, empirically evaluate the SMOTE over-sampling approaches, AdaBoost and random forests algorithm. We also discuss the approaches for selecting features. Finally report our experimental results over the KDD'99 datasets. The results show that SMOTE and the AdaBoost Algorithm by using random forests as weak learner not only can provides better performance to small class, but also has lower build model time.
Technical communique: H2 control of continuous-time uncertain linear systems with input quantization and matched disturbances
Authors: Sung Wook Yun, Yun Jong Choi, PooGyeon Park
Venue: Automatica (Journal of IFAC) (2009)

For uncertain linear systems with input quantization and matched disturbances, this paper introduces an H"2 state-feedback controller, which comprises linear and nonlinear parts. The former part plays a role in determining the fundamental characteristics of the system against model uncertainties. The latter part eliminates the effect of input quantization and matched disturbances. In other words, each component of the latter part is designed as an integer multiple of the quantization level, which provides a clue to maintaining the decreasing property of a Lyapunov function, associated with the H"2 cost, despite input quantization and matched disturbances.
On the Feasibility of Dynamically Scheduling DAG Applications on Shared Heterogeneous Systems
Authors: Aline P. Nascimento, Alexandre Sena, Cristina Boeres, Vinod E. Rebello
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

Grid and Internet Computing have proved their worth executing large-scale bag-of-task class applications. Numerous middlewares have been developed to manage their execution in either dedicated environments or opportunistic and shared ad-hoc grids. While job dependencies are now being resolved by middleware capable of scheduling workflows, these environments have yet to be shown beneficial for message passing parallel applications. Obtaining high performance in these widely available environments without rewriting existing parallel applications is of up most importance to e-Science. The key to an efficient solution may be an alternative execution model and the efficient dynamic scheduling of application processes. This paper presents a hierarchical scheme for dynamically scheduling parallel DAG applications across a set of non-dedicated heterogeneous resources. In order to efficiently tackle process dependencies and adapt to varying system characteristics, dynamic schedulers are distributed within the application and operate in a collaborative and pro-active fashion to keep overheads low.
Plant Species Identification Using Multi-scale Fractal Dimension Applied to Images of Adaxial Surface Epidermis
Authors: André R. Backes, Jarbas J. M. Sá Junior, Rosana M. Kolb, Odemir M. Bruno
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

This paper presents the study of computational methods applied to histological texture analysis in order to identify plant species, a very difficult task due to the great similarity among some species and presence of irregularities in a given species. Experiments were performed considering 300 ×300 texture windows extracted from adaxial surface epidermis from eight species. Different texture methods were evaluated using Linear Discriminant Analysis (LDA). Results showed that methods based on complexity analysis perform a better texture discrimination, so conducting to a more accurate identification of plant species.
Intuitive Visualization-Oriented Metamodeling
Authors: Dirk Draheim, Melanie Himsl, Daniel Jabornig, Werner Leithner, Peter Regner, Thomas Wiesinger
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

In this article we present a metamodeling tool that is strictly oriented towards the needs of the working domain expert. The working domain expert longs for intuitive metamodeling features. In particular this concerns rich capabilities for specifying the visual appearance of models. In these efforts we have identified an important design rationale for metamodeling tools that we call visual reification --- the notion that metamodels are visualized the same way as their instances. In our tool we support both, standard metamodeling features and new metamodeling features that are oriented towards the visual reification principle. We will start an unbiased discussion of the pragmatics of metamodeling tools against the background of this design rationale.
Component-Based Abstraction in Fault Tree Analysis
Authors: Dominik Domis, Mario Trapp
Venue: Proceedings of the 28th International Conference on Computer Safety, Reliability, and Security (2009)

To handle the complexity of safety-critical embedded systems, it is not appropriate to develop functionality and consider safety in separate tasks, or to consider software only as a black box in safety analyses. Rather, safety aspects have to be integrated as tightly as possible into the system and software development process and its models. But existing safety analyses and models do not fit well with software development tasks such as architectural design and do not take advantage of their strengths. To solve this problem, this paper extends fault tree analysis by hierarchical component-based abstraction, enabling fault tree analysis to be integrated into a component-oriented model-based design approach and to handle the complexity of software architectural design.
A logic built-in self-test architecture that reuses manufacturing compressed scan test patterns
Authors: Diogo José Costa Alves, Edna Barros
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

The claim for new functionalities regarding the improvement of dependability of electronic systems and also the need for managing the time spent during test make the Built-in-Self-Test mechanism (BIST) a promising feature to be integrated in current IC flows. There are a lot of types of BIST: Memories BIST, Logical BIST (LBIST) and also some mechanisms used to test analog parts of circuit. Traditional LBIST uses on-chip hardware to generate all test patterns with a pseudo-random-pattern-generator (PRPG) and analyzes the output signature generated by a multiple-input-signature-register (MISR). This approach requires the insertion of extra test-points or storing information outside chip to enable achieving a test coverage >98%. Also generating all test stimuli implies in a sacrifice of test application time, which can be acceptable for some small systems to perform self-test during boot up but could become a negative aspect when testing System-on-chip (SOC) ICs. The current IC development flow insert scan chains and generates automatically scan tests patterns to achieve high fault coverage for manufacturing test. Scan data compression techniques have proven to be very useful for reducing test cost while reducing test data volume and test application time. This work proposes the reuse of compressed scan test patterns used during manufacturing test to implement a LBIST with the goal of testing the circuit when it is already in field. The proposed LBIST mechanism aims to uncover defects that could occur due to the wear out of the circuit. A scan test pattern based LBIST architecture and a semi-automatic development flow are proposed and validated in a real word SoC testcase.
The Invariant Functions of the Rational Bi-cubic Bézier Surfaces
Authors: H. E. Bez
Venue: Proceedings of the 13th IMA International Conference on Mathematics of Surfaces XIII (2009)

Patterson's work [1] on the invariants of the rational Bézier paths may be extended to permit weight vectors of mixed-sign [2]. In this more general situation, in addition to Patterson's continuous invariants, a discrete sign-pattern invariant is required to distinguish path geometry. The author's derivation of the invariants differs from that of Patterson's and extends naturally to the rational Bézier surfaces. In this paper it is shown that 13 continuous invariant functions and a discrete, sign-pattern, invariant exist for the bi-cubic surfaces. Explicit functional forms of the invariant functions for the bi-cubics are obtained. The results are viewed from the perspective of the Fundamental Theorem on invariants for Lie groups.
A software tool for teaching reading based on text-to-speech letter-to-phoneme rules
Authors: Marian J. Macchi, Dan Kahn
Venue: Proceedings of the second workshop on Building Educational Applications Using NLP (2005)

Native speakers of English who are good readers can "sound out" words or names from printed text, even if they have never seen them before, although they may not be conscious of the strategies they use. No tools are available today that can convey that knowledge to learners, showing them the rules that apply in English text. We have adapted the letter-to-phoneme component of a text-to-speech synthesizer to a web-based software system that can teach word decoding to non-native speakers of English, English-speaking children, and adult learners.
A learning-based term-weighting approach for information retrieval
Authors: GuangCan Liu, Yong Yu, Xing Zhu
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

One of the core components in information retrieval (IR) is the document-term-weighting scheme. In this paper, we will propose a novel learning-based term-weighting approach to improve the retrieval performance of vector space model in homogeneous collections. We first introduce a simple learning system to weighting the index terms of documents. Then, we deduce a formal computational approach according to some theories of matrix computation and statistical inference. Our experiments on 8 collections will show that our approach out-performs classic tfidf weighting, about 20%-45%.
Evaluating the communication design of branded websites: a value-based framework
Authors: Davide Bolchini, Tao Yang, Franca Garzotto
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

The quality of web communication depends on several factors. One of these, besides usability, is the effectiveness by which the intended brand values are actually conveyed to the users. Leveraging existing research in web branding communication, design and requirements engineering, we propose a systematic framework for evaluating the short-term communication impact of large, information-intensive branded websites. The communication impact is empirically investigated by eliciting and modeling the brand values that the website tries to convey and assessing whether and how much they are perceived by the intended target users. Results from two case studies show that simple and readable indicators can be constructed to identify flaws in the communication of the brand values and support designers and stakeholders to devise precise strategies to improve the design accordingly.
Vulnerability Assessment of Regional Water Distribution Systems
Authors: Zhuang Baoyu, Zhao Xinhua, Zhao Yuan
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

A vulnerability assessment model for regional water distribution system (VAMRWDS) is presented. The model takes into account the impact of residual chlorine and water age, as well as the uncertainty and probabilistic characteristic of the distribution systems. Monte-Carlo stochastic simulation is adopted in the model to randomly generate bulk and wall reaction coefficients. Employing the EPANET toolkit as the hydraulic and water quality solver, the model can identify the vulnerable zones and calculate the vulnerability index of each junction and the entire system. VAMRWDS is demonstrated on an example application of a planed regional water distribution system in northern China and the results show the rationality and efficiency of the model.
The painful face - Pain expression recognition using active appearance models
Authors: Ahmed Bilal Ashraf, Simon Lucey, Jeffrey F. Cohn, Tsuhan Chen, Zara Ambadar, Kenneth M. Prkachin, Patricia E. Solomon
Venue: Image and Vision Computing (2009)

Pain is typically assessed by patient self-report. Self-reported pain, however, is difficult to interpret and may be impaired or in some circumstances (i.e., young children and the severely ill) not even possible. To circumvent these problems behavioral scientists have identified reliable and valid facial indicators of pain. Hitherto, these methods have required manual measurement by highly skilled human observers. In this paper we explore an approach for automatically recognizing acute pain without the need for human observers. Specifically, our study was restricted to automatically detecting pain in adult patients with rotator cuff injuries. The system employed video input of the patients as they moved their affected and unaffected shoulder. Two types of ground truth were considered. Sequence-level ground truth consisted of Likert-type ratings by skilled observers. Frame-level ground truth was calculated from presence/absence and intensity of facial actions previously associated with pain. Active appearance models (AAM) were used to decouple shape and appearance in the digitized face images. Support vector machines (SVM) were compared for several representations from the AAM and of ground truth of varying granularity. We explored two questions pertinent to the construction, design and development of automatic pain detection systems. First, at what level (i.e., sequence- or frame-level) should datasets be labeled in order to obtain satisfactory automatic pain detection performance? Second, how important is it, at both levels of labeling, that we non-rigidly register the face?
Simulation of a P2P Application Using OverSim
Authors: Juan Pedro Munoz-Gea, Josemaria Malgosa-Sanahuja, Pilar Manzanares-Lopez, Juan Carlos Sanchez-Aarnoutse, Antonio M. Martinez-Rojo
Venue: Proceedings of the 2009 First International Conference on Advances in Future Internet (2009)

OverSim is a new open-source overlay network simulation framework based on the discrete event simulation system OMNeT++. OverSim includes several structured and unstructured P2P (peer-to-peer) protocols. It also includes an underlay model derived from the INET framework of OMNeT++, which includes simulation models of all network layers from the MAC layer onwards. For this and other reasons, this framework overcomes several drawbacks of existing P2P simulators, and it is considered one of the most powerful tools for the research community. This paper contains a very low-level description of the simulation of a particular P2P application using OverSim. It also contains information about how to use it in general P2P simulations.The aim is to provide an introduction to this powerful tool for the workers in the field of P2P networking.
Detecting Intentional Errors Using the Pressures Applied to a Computer Mouse
Authors: Curtis Ikehara, Martha E. Crosby
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Intentional errors are considered a form of deceit. In this pilot study, the pressures applied to a computer mouse will be analyzed to determine if it is possible to detect intentional errors. Twenty participants ranging in age from 18 to 21 years performed a task involving intentionally making errors when instructed. A comparison will be made between the pressures applied to a computer mouse when answering the questions with the intention of being correct and with the intention of making an error. The data will need to be normalized for each individual to obtain accurate results. The analysis of the pressures may indicate that there are detectable variations within some individuals. Due to the preliminary nature of this study further research will be required.
Characterizing the Psychophysiological Profile of Expert and Novice Marksmen
Authors: Nicholas Pojman, Adrienne Behneman, Natalie Kintz, Robin Johnson, Greg Chung, Sam Nagashima, Paul Espinosa, Chris Berka
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Marksmanship training includes a combination of classroom instruction and field practice involving the instantiation of a well-defined set of sensory, motor, and cognitive skills. 10 expert marksmen and 30 novices participated in a study that measured marksman performance during simulated ballistics shooting of a M4 replica infrared rifle. Participants' physiology and performance were quantified while they completed a battery of neurocognitive tests. Experts demonstrated consistent and more accurate shot performance across all trials. Compared to novices, experts evidenced lower levels of sympathetic activation as measured by heart rate variability during the neurocognitive tasks. Factor analysis identified experts as having above normal visuospatial processing speeds and sustained attention, reflecting experts as having better performance during vigilance neurocognitive tasks. Identifying physiological metrics of experts during neurocognitive testing opens the door to individualized novice instruction to help to improve specific areas flagged as below normal during or prior to novice marksmanship instruction.