ppxscal/embedding_network huggingface dataset:
Minimizing environmental swings with a recurrent neural network control system
Authors: Sam Skrivan, Jianna Zhang, Debra Jusak
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

Maintaining environmental stability in a dynamic system is a difficult challenge. In your living room, when you set your thermostat to 68 degrees the actual temperature cycles above and below 68 degrees. We attempt to use a Recurrent Neural Network (RNN) in an Aquarium Control System that reduces such environmental swings.
Gorgias-C: Extending Argumentation with Constraint Solving
Authors: Victor Noël, Antonis Kakas
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

GORGIAS-C is a system implementing a logic programming framework of argumentation that integrates together preference reasoning and constraint solving.The framework of argumentation with preference reasoning [1,2] was first implemented in the GORGIAS system which hasmainly been used in the multi-agent domain [2,3,4], medical informatics [5] and network security [6].
Geometric structure-preserving optimal control of a rigid body
Authors: A. M. Bloch, I. I. Hussein, M. Leok, A. K. Sanyal
Venue: Journal of Dynamical and Control Systems (2009)

In this paper, we study a discrete variational optimal control problem for a rigid body. The cost to be minimized is the external torque applied to move the rigid body from an initial condition to a pre-specified terminal condition. Instead of discretizing the equations of motion, we use the discrete equations obtained from the discrete Lagrange---d'Alembert principle, a process that better approximates the equations of motion. Within the discrete-time setting, these two approaches are not equivalent in general. The kinematics are discretized using a natural Lie-algebraic formulation that guarantees that the flow remains on the Lie group SO(3) and its algebra $\mathfrak{s}\mathfrak{o}(3)$ . We use the Lagrange method for constrained problems in the calculus of variations to derive the discrete-time necessary conditions. We give a numerical example for a three-dimensional rigid body maneuver.
Engineering Countermeasures to Reducing Red-Light Running
Authors: Hong-bo Qian, Yu-pu Dong
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

Red-light running problem has been recognized as a significant safety problem in China as well as throughout the world and can be categorized either deliberate or unintentional. By analyzing the driver behavior at the end of green phase, the factors affecting unintentional red-light running and engineering countermeasures are put forward, including signal operation countermeasures, motorist information countermeasures, and physical improvement countermeasures. The research indicates that engineering countermeasures can decreased unintentional red-light running and should receive priority over automated enforcement for addressing red-light running problems.
VolpexMPI: An MPI Library for Execution of Parallel Applications on Volatile Nodes
Authors: Troy Leblanc, Rakhi Anand, Edgar Gabriel, Jaspal Subhlok
Venue: Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2009)

The objective of this research is to convert ordinary idle PCs into virtual clusters for executing parallel applications. The paper introduces VolpexMPI that is designed to enable seamless forward application progress in the presence of frequent node failures as well as dynamically changing networks speeds and node execution speeds. Process replication is employed to provide robustness in such volatile environments. The central challenge in VolpexMPI design is to efficiently and automatically manage dynamically varying number of process replicas in different states of execution progress. The key fault tolerance technique employed is fully distributed sender based logging. The paper presents the design and a prototype implementation of VolpexMPI. Preliminary results validate that the overhead of providing robustness is modest for applications having a favorable ratio of communication to computation and a low degree of communication.
Ibis: A Programming System for Real-World Distributed Computing
Authors: Henri Bal
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

The landscape of distributed computing systems has changed many times over the previous decades. Modern real-world distributed systems consist of clusters, grids, clouds, desktop grids, and mobile devices. Writing applications for such systems has become increasingly difficult. The aim of the Ibis project is to drastically simplify the programming of such applications. The Ibis philosophy is that real-world distributed applications should be developed and compiled on a local workstation, and simply be launched from there.The Ibis project studies several fundamental problems of distributed computing hand-in-hand with major applications, and integrates the various solutions in one programming system. Applications that drive the Ibis project include scientific ones (in the context of the VL-e project), multimedia content analysis, distributed reasoning, and many others. The fundamental problems we study include performance, heterogeneity, malleability, fault-tolerance, and connectivity. Solutions to these fundamental problems are integrated in the Ibis programming system, which is written entirely in Java. Examples are: runtime systems for many programming models (divide-and-conquer, master-worker, etc.), a Java-centric communication library (IPL), a library that automatically solves connectivity problems (SmartSockets), a graphical deployment system, a library that hides the underlying middlewares (JavaGAT), and a simple peer-to-peer middleware (Zorilla). The resulting system has been used in several award-winning competitions, including SCALE 2008 (at CCgrid'08) and DACH 2008 (at Cluster/Grid'08).The talk describes the rationale behind Ibis, the main applications (in particular multimedia content analysis), and its most important software components. Next, it discusses experiments where Ibis is used to run parallel applications efficiently on a large-scale distributed system consisting of several clusters, a desktop grid, and an Amazon cloud. Finally, the talk discusses recent work in using Ibis for distributed applications that run on mobile devices (smart phones) or that deploy distributed applications from a mobile device. An example is given where a distributed object-recognition application is launched from an Android phone, so the user can perform tasks that would be impossible on the limited resources of the phone itself.For more information on Ibis, please see http://www.cs.vu.nl/ibis/.
Zero Watermark Protocol Based on Time-Stamp and Digital Signature
Authors: Hu Chaoju, Wang Xuning
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Zero watermark is a new research direction of the digital watermark technique. It availably solves the antinomy between robustness and imperceptibility, and protects the copyright of image better. On the basis of the attacks the application of digital watermark is facing and the existence of security risks of DHWM Protocol, in this paper we put forward a new safe zero watermark Protocol based on time-stamp and digital signature. The protocol introduces digital certificate, through the extraction of important information in images to generate zero watermark with digital signature and time-stamp as specific information. The Protocol can resist intermediary attacks and explain attacks through security analysis and performance analysis, with no real sense of visibility and high security it can be applied to the actual copyright protection of digital image.
A geometric interpretation of non-target-normalized maximum cross-channel correlation for vocal activity detection in meetings
Authors: Kornel Laskowski, Tanja Schultz
Venue: Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX (2007)

Vocal activity detection is an important technology for both automatic speech recognition and automatic speech understanding. In meetings, standard vocal activity detection algorithms have been shown to be ineffective, because participants typically vocalize for only a fraction of the recorded time and because, while they are not vocalizing, their channels are frequently dominated by crosstalk from other participants. In the present work, we review a particular type of normalization of maximum cross-channel correlation, a feature recently introduced to address the crosstalk problem. We derive a plausible geometric interpretation and show how the frame size affects performance.
Application of Triangulation-Based Image Registration Method in the Remote Sensing Image Fusion
Authors: Lin Xuehua, Zhang Yongzhi, Yang YuJiazi
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Based on image registration principle of the feature point, this article brings forward methods of a combination of Moravec and Forstner operator, extracts feature points in the base image making use of sequential detection algorithm from coarse to fine, and realizes automatic matching of the same name point in the pending registration images through the geometric distance constraint conditions. After the triangulation through the triangulation methods in this article, the images and the results by the second transformation method have similar performance, but in the process of registration it can save a lot of time and energy. Count the three aspects of information including entropy, degrees of spectral distortion and into-degrees of high-frequency information in the fused image. Of which entropy expresses the amount of images information. The value of entropy in the fused image is larger than the original panchromatic image and multi-spectral image, accounting for through the image fusion it indeed improves the information content of the image! In Shenzhen City Digital City project, the results by using of the method showed that the fusion effect is significantly higher than other traditional methods.
Fault Detection and Diagnosis Based on KPCA-LSSVM Model
Authors: Zhonghai Li, Yan Zhang, Liying Jiang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

Although Kernel Principle Component Analysis（KPCA）has been used to monitoring nonlinear processes, it is not well suited for fault diagnosis. In order to solve this problem, a new method of fault detection and diagnosis for nonlinear processes based on KPCA and Least Squares Support Vector Machine(LSSVM) is proposed. The KPCA is used to monitor faults and extract feature and LSSVM model is used to diagnose fault, LSSVM model is constructed based on nonlinear principle component scores of various known faults. The applications in TE process illustrate the efficiency of the proposed approach.
IR Evaluation without a Common Set of Topics
Authors: Matteo Cattelan, Stefano Mizzaro
Venue: Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory (2009)

Usually, system effectiveness evaluation in a TREC-like environment is performed on a common set of topics. We show that even when using different topics for different systems, a reliable evaluation can be obtained, and that reliability increases by using appropriate topic selection strategies and metric normalizations.
Memory-based morphological analysis generation and part-of-speech tagging of Arabic
Authors: Erwin Marsi, Antal van den Bosch, Abdelhadi Soudi
Venue: Proceedings of the ACL Workshop on Computational Approaches to Semitic Languages (2005)

We explore the application of memory-based learning to morphological analysis and part-of-speech tagging of written Arabic, based on data from the Arabic Treebank. Morphological analysis -- the construction of all possible analyses of isolated unvoweled wordforms -- is performed as a letter-by-letter operation prediction task, where the operation encodes segmentation, part-of-speech, character changes, and vocalization. Part-of-speech tagging is carried out by a bi-modular tagger that has a subtagger for known words and one for unknown words. We report on the performance of the morphological analyzer and part-of-speech tagger. We observe that the tagger, which has an accuracy of 91.9% on new data, can be used to select the appropriate morphological analysis of words in context at a precision of 64.0 and a recall of 89.7.
Translation model pruning via usage statistics for statistical machine translation
Authors: Matthias Eck, Stephan Vogel, Alex Waibel
Venue: Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX (2007)

We describe a new pruning approach to remove phrase pairs from translation models of statistical machine translation systems. The approach applies the original translation system to a large amount of text and calculates usage statistics for the phrase pairs. Using these statistics the relevance of each phrase pair can be estimated. The approach is tested against a strong baseline based on previous work and shows significant improvements.
Steering of sequential jobs with a distributed shared memory based model for online steering
Authors: Daniel Lorenz, Peter Buchholz, Christian Uebing, Wolfgang Walkowiak, Roland Wismüller
Venue: Future Generation Computer Systems (2010)

Online steering systems allow one to retrieve application data like intermediate results for visualization, and to modify parameters during the run-time of the application. While most steering systems use a client/server paradigm, online steering can favorably be modeled as a distributed shared memory with concurrent access by the application and the online steerer. In this paper, this idea is formalized, focusing on the exploration of the consistency models and protocols for the distributed shared memory. The behavior of the steering system is described by consistency models, which also guarantee the data integrity of the application, both within a single process and between multiple application processes. Depending on the integrity requirements, applications can choose the proper model and protocol. The performance of our protocols is evaluated with a synthetic workload, which shows that the newly developed delayed weak consistency is faster than the special weak consistency. Furthermore, the results prove that the invalidate protocols of both consistency models are able to adapt themselves to the workload.
An analysis of active learning strategies for sequence labeling tasks
Authors: Burr Settles, Mark Craven
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but annotation is slow and expensive. This paper aims to shed light on the best active learning approaches for sequence labeling tasks such as information extraction and document segmentation. We survey previously used query selection strategies for sequence models, and propose several novel algorithms to address their shortcomings. We also conduct a large-scale empirical comparison using multiple corpora, which demonstrates that our proposed methods advance the state of the art.
Research on Model and Its Solving Algorithm for Transit Scheduling Problem
Authors: YongFeng Dong, NaNa Li, ZhengChao Dong, Junhua Gu, Weini Li
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

This paper described the way of generating a reasonable bus scheduling, so that getting the lowest operating costs, the shortest waiting time for average passenger and the smallest vehicle demand in some bus lines of regional area. To achieve information resource and transport ability sharing, the transit regional scheduling optimization model is set up, and solved by hybrid simulated annealing/genetic algorithm for the different intervals and the different number in the region line of the departure times of the day. The experiment results showed that the model and the algorithm are feasibility and effective
Development of the Powertrain Control System for Four Wheel Driven Hybrid Electric Vehicle
Authors: Gu Jiading, Zhao Zhiguo, Yu Zhuoping
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

Powertrain control system for “step I” four-wheel driven hybrid electric vehicle has been developed, in which the front wheels are driven by conversional engine through automatic transmission and the rear wheels are directively driven by in-wheel motors. Firstly, hardware of the controller is designed using XC167CI chip with TouCAN structure. The bottom-level driven software of the controller is generated and compiled through comprehensively use of tool packages such as Dave and Tasking C. Secondly, different working modes of powertrain system are subdivided, and the energy management strategy based on logic threshold value control is implemented through application of Matlab Stateflow. Finally, on-board vehicle test of the powertrain control system is carried through using test methods of hardware-in-the-loop (HIL) and Bypass. The test results illustrate the feasibility and validity of the above powertrain control system.
Electromagnetic Flowmeter Measurement and Numerical Computation of Laminar Flow Transport Pipeline Flow Quantity
Authors: Xia Yuming, Xu Zhiqiang
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Electromagnetic flowmeter was adopted to measure the flow quantity of coal water slurry (CWS) transport pipeline, and the average flow velocity of pipeline was calculated by using the measured inductive electromotive force value. Then the Reynolds number of fluid in the pipeline was calculated and the fluid in the CWS transport pipeline was proved to be flowing in the laminar flow state. The axial velocity of the axial flow field of CWS transport pipeline flowing in the laminar flow state was obtained by using the finite element method. The distribution of axial velocity in the CWS transport pipeline and the relationship curve between axial velocity and cross sectional diameter of pipeline axial flow field were drawn in two-dimensional plane separately. Finally, the actual average velocity and flow quantity measured by electromagnetic flowmeter and the numerical average velocity and flow quantity computed by finite element method were compared, according to the comparison results, the relative error between the average velocity measured by electromagnetic flowmeter and the average velocity computed by the finite element methods is less than 1%, and the relative error between the flow quantity measured by electromagnetic flowmeter and the flow quantity computed by the finite element methods is either less than 1%.
EXSTASIS --- An Extended Status Model for Social Interactions
Authors: Martin Rumpler
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

In this article we show how socio-psychological status theories can be formalized and used to control the expressive and communicative behavior of intelligent virtual agents. We describe Exstasis, a model that computes the status and action tendencies for all actors in a situation based on their status characteristics and behavior patterns. As a configurable software component Exstasis can be integrated in existing systems to extend the social capabilities of the virtual characters. 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
Robust supervised learning
Authors: J. Andrew Bagnell
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

Supervised machine learning techniques developed in the Probably Approximately Correct, Maximum A Posteriori, and Structural Risk Minimiziation frameworks typically make the assumption that the test data a learner is applied to is drawn from the same distribution as the training data. In various prominent applications of learning techniques, from robotics to medical diagnosis to process control, this assumption is violated. We consider a novel framework where a learner may influence the test distribution in a bounded way. From this framework, we derive an efficient algorithm that acts as a wrapper around a broad class of existing supervised learning algorithms while guarranteeing more robust behavior under changes in the input distribution.
Constraint-Driven Instructions Selection and Application Scheduling in the DURASE system
Authors: Kevin Martin, Christophe Wolinski, Krzysztof Kuchcinski, Antoine Floch, Francois Charot
Venue: Proceedings of the 2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors (2009)

This paper presents a new constraint-driven method for computational pattern selection, mapping and application scheduling using reconfigurable processor extensions. The presented method is a part of DURASE system (Generic Environment for Design and Utilization of Reconfigurable Application-Specific Processors Extensions).The selected processor extensions are implemented as specialized processor instructions. They correspond to computational patterns identified as most frequently occurring or other interesting patterns in the application graph. Our methods can handle both time-constrained and resource-constrained scheduling. Experimental results obtained for the MediaBench and MiBench benchmarks show that the presented method ensures high speed-ups in application execution.
Visualization and Clustering of Business Process Collections Based on Process Metric Values
Authors: Joachim Melcher, Detlef Seese
Venue: Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2008)

Motivated by ideas of software measurement, the area of process measurement has attracted attention in recent time. Numerous process metrics have been proposed to measure (often structural) properties of business processes.In this paper, we propose heatmaps, a visualization technique for high-dimensional data originally used in genetics, for visualizing the process metric values of business process collections. So, new insights into the distribution of the metric values among the processes could be gained. Additionally, we use clustering for analyzing (1) the correlations between different process metrics and (2) finding (structurally) similar processes among business process collections. Our approach has been successfully applied to the SAP Reference Model processes.