ppxscal/embedding_network huggingface dataset:
Evaluation of automated-trading strategies using an artificial market
Authors: K. Izumi, F. Toriumi, H. Matsui
Venue: Neurocomputing (2009)

The purpose of this study was to extend the simulation of artificial markets to the practical application. We constructed an artificial-market system with an interface with the automated-trading strategies. Then, using an artificial-market simulation, we conducted two types of evaluations of automated-trading strategies that could participate in a Kaburobo competition. (1) Our system evaluated the risks and returns of the strategies in various market environments. An evaluation using the artificial market was able to provide better information than a conventional evaluation using a back test. (2) Our system could also test the market impact of automated-trading strategies. Our results revealed that the market impact of the strategies may not only depend on their rule content but also on the way they are combined with other strategies.
Detection of non-native sentences using machine-translated training data
Authors: John Lee, Ming Zhou, Xiaohua Liu
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)

Training statistical models to detect non-native sentences requires a large corpus of non-native writing samples, which is often not readily available. This paper examines the extent to which machine-translated (MT) sentences can substitute as training data. Two tasks are examined. For the native vs non-native classification task, non-native training data yields better performance; for the ranking task, however, models trained with a large, publicly available set of MT data perform as well as those trained with non-native data.
Nonmyopic informative path planning in spatio-temporal models
Authors: Alexandra Meliou, Andreas Krause, Carlos Guestrin, Joseph M. Hellerstein
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

In many sensing applications we must continuously gather information to provide a good estimate of the state of the environment at every point in time. A robot may tour an environment, gathering information every hour. In a wireless sensor network, these tours correspond to packets being transmitted. In these settings, we are often faced with resource restrictions, like energy constraints. The users issue queries with certain expectations on the answer quality. Thus, we must optimize the tours to ensure the satisfaction of the user constraints, while at the same time minimize the cost of the query plan. For a single timestep, this optimization problem is NP-hard, but recent approximation algorithms with theoretical guarantees provide good solutions. In this paper, we present a new efficient algorithm, exploiting dynamic programming and submodularity of the information collected, that efficiently plans data collection tours for an entire (finite) horizon. Our algorithm can use any single step procedure as a black box, and, based on its properties, provides strong theoretical guarantees for the solution. We also provide an extensive empirical analysis demonstrating the benefits of nonmyopic planning in two real world sensing applications.
Dynamic Load Balancing of Matrix-Vector Multiplications on Roadrunner Compute Nodes
Authors: José Carlos Sancho, Darren J. Kerbyson
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

Hybrid architectures that combine general purpose processors with accelerators are currently being adopted in several large-scale systems such as the petaflop Roadrunner supercomputer at Los Alamos. In this system, dual-core Opteron host processors are tightly coupled with PowerXCell 8i accelerator processors within each compute node. In this kind of hybrid architecture, an accelerated mode of operation is typically used to off-load performance hotspots in the computation to the accelerators. In this paper we explore the suitability of a variant of this acceleration mode in which the performance hotspots are actually shared between the host and the accelerators. To achieve this we have designed a new load balancing algorithm, which is optimized for the Roadrunner compute nodes, to dynamically distribute computation and associated data between the host and the accelerators at runtime. Results are presented using this approach, for sparse and dense matrix-vector multiplications, that show load-balancing can improve performance by up to 24% over solely using the accelerators.
CLaC and CLaC-NB: knowledge-based and corpus-based approaches to sentiment tagging
Authors: Alina Andreevskaia, Sabine Bergler
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

For the Affective Text task at Semeval-1/Senseval-4, the CLaC team compared a knowledge-based, domain-independent approach and a standard, statistical machine learning approach to ternary sentiment annotation of news headlines. In this paper we describe the two systems submitted to the competition and evaluate their results. We show that the knowledge-based unsupervised method achieves high accuracy and precision but low recall, while supervised statistical approach trained on small amount of in-domain data provides relatively high recall at the cost of low precision.
Mutual belief revision: semantics and computation
Authors: Yi Jin, Michael Thielscher, Dongmo Zhang
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

This paper presents both a semantic and a computational model for multi-agent belief revision. We show that these two models are equivalent but serve different purposes. The semantic model displays the intuition and construction of the belief revision operation in multi-agent environments, especially in case of just two agents. The logical properties of this model provide strong justifications for it. The computational model enables us to reassess the operation from a computational perspective. A complexity analysis reveals that belief revision between two agents is computationally no more demanding than single agent belief revision.
Exploiting the Cell/BE Architecture with the StarPU Unified Runtime System
Authors: Cédric Augonnet, Samuel Thibault, Raymond Namyst, Maik Nijhuis
Venue: Proceedings of the 9th International Workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2009)

Core specialization is currently one of the most promising ways for designing power-efficient multicore chips. However, approaching the theoretical peak performance of such heterogeneous multicore architectures with specialized accelerators, is a complex issue. While substantial effort has been devoted to efficiently offloading parts of the computation, designing an execution model that unifies all computing units is the main challenge.We therefore designed the StarPU runtime system for providing portable support for heterogeneous multicore processors to high performance applications and compiler environments. StarPU provides a high-level, unified execution model which is tightly coupled to an expressive data management library. In addition to our previous results on using multicore processors alongside with graphic processors, we show that StarPU is flexible enough to efficiently exploit the heterogeneous resources in the Cell processor. We present a scalable design supporting multiple different accelerators while minimizing the overhead on the overall system. Using experiments with classical linear algebra algorithms, we show that StarPU improves programmability and provides performance portability.
Cognition and the temporal arts: Investigating audience response to dance using PDAs that record continuous data during live performance
Authors: Catherine J. Stevens, Emery Schubert, Rua Haszard Morris, Matt Frear, Johnson Chen, Sue Healey, Colin Schoknecht, Stephen Hansen
Venue: International Journal of Human-Computer Studies (2009)

If artists and art explore organization of the brain [Zeki, S., Lamb, M., 1994. The neurology of kinetic art. Brain 117, 607-636], then investigation of response to artistic performance holds promise as a window to perceptual and cognitive processes. A new instrument for recording real-time audience response - the portable Audience Response Facility (pARF) - is described. Twenty, hand-held, Personal Digital Assistants (PDAs) collect responses on customizable skin interfaces. The pARF server transmits the customizable options, synchronizes devices and collects data for export. We report two studies using the pARF that demonstrate respondent agreement of perceived emotion during particular sections of two dance works. Greater agreement was evident in continuous ratings of arousal than valence; arousal appears to be related to surface features of the dance work. Future applications of the pARF to studies of multi-modal perception and cognition are discussed.
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation
Authors: Jeff Johns, Marek Petrik, Sridhar Mahadevan
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

The goal of approximate policy evaluation is to "best" represent a target value function according to a specific criterion. Different algorithms offer different choices of the optimization criterion. Two popular least-squares algorithms for performing this task are the Bellman residual method, which minimizes the Bellman residual, and the fixed point method, which minimizes the projection of the Bellman residual. When used within policy iteration, the fixed point algorithm tends to ultimately find better performing policies whereas the Bellman residual algorithm exhibits more stable behavior between rounds of policy iteration. We propose two hybrid least-squares algorithms to try to combine the advantages of these algorithms. We provide an analytical and geometric interpretation of hybrid algorithms and demonstrate their utility on a simple problem. Experimental results on both small and large domains suggest hybrid algorithms may find solutions that lead to better policies when performing policy iteration.
XML Lossy Text Compression: A Preliminary Study
Authors: Angela Bonifati, Marianna Lorusso, Domenica Sileo
Venue: Proceedings of the 6th International XML Database Symposium on Database and XML Technologies (2009)

Lossy compression techniques have been applied to image and text compression, yielding compression factors that are vastly superior to lossless compression schemes. In this paper, we present a preliminary study on a set of lossy transformations for XML documents that preserve the semantics. Inspired by previous techniques, e.g. lossy text compression and literate programming, we apply a simple algorithm to XML syntactic constructs to loose superfluous layout information and redundant text. The obtained XML keeps the human-readability and machine-readability properties. Additionally, it can lead to a considerable reduction of its space occupancy and boost the application of conventional text compressors, thus representing a promising technology for several data management tasks.
Rapidly Prototyping Marker Based Tangible User Interfaces
Authors: Maribeth Gandy, Brian Jones, Scott Robertson, Tiffany O`Quinn, Amos Johnson
Venue: Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009 (2009)

Tangible user interfaces (TUIs) can create engaging and useful interactive systems. However, along with the power of these interfaces comes challenges; they are often so specialized and novel that building a TUI system involves working at a low level with custom hardware and software. As a result the community of people that are capable of creating TUIs is limited. With this project we aim to make a particular class of TUIs accessible to a broader range of designers and HCI researchers by exposing TUI specific tools in a mixed-reality rapid prototyping environment know as DART (The Designer's Augmented Reality Toolkit). In this paper we discuss the creation of a system for rapidly prototyping marker based tangible user interfaces. These prototyping tools were then used to create a set of TUI-based applications with the goal of raising students' interest in science via an exploration of fine art concepts.
Safe Runtime Verification of Real-Time Properties
Authors: Christian Colombo, Gordon J. Pace, Gerardo Schneider
Venue: Proceedings of the 7th International Conference on Formal Modeling and Analysis of Timed Systems (2009)

Introducing a monitor on a system typically changes the system's behaviour by slowing the system down and increasing memory consumption. This may possibly result in creating new bugs, or possibly even `fixing' bugs, only to reappear as the monitor is removed. Properties written in a real-time logic, such as duration calculus, can be particularly sensitive to such changes induced through monitoring. The same problem occurs in other scenarios such as when a system is ported to a faster machine. In this paper, we identify a class of real-time properties, in duration calculus, which are monotonic under the slowing down (speeding up) of the underlying system. We apply this approach to the real-time runtime monitoring tool Larva, where we use duration calculus as a monitoring property specification language, so we automatically identify properties which can be shown to be monotonic with respect to system re-timing.
Interval event stream processing
Authors: Ming Li, Murali Mani, Elke A. Rundensteiner, Di Wang, Tao Lin
Venue: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems (2009)

Event stream processing (ESP) has become increasingly important in modern applications, ranging from supply chain management to real-time intrusion detection. Existing ESP engines have focused on detecting temporal patterns from instantaneous events, that is, events with no duration. Under such a model, an event instance can only be happening "before", "after" or "at the same time as" another event instance. However, such sequential patterns are inadequate to express the complex temporal relationships in domains such as medical, finance and meteorology, where the events' durations could play an important role.
A flexible and scalable message broker for sensor network integration
Authors: Luis Garcés-Erice, Daniel Bauer, Paolo Scotton
Venue: Proceedings of the Fourth International ICST Conference on COMmunication System softWAre and middlewaRE (2009)

Sensor network technologies have experienced an enormous development with the proliferation of sensor devices, custom communication protocols, and methods to exploit the data gathered on such networks. The actual impact of this technology on the enterprise, however, has been quite limited. This is because the community has focused almost exclusively on the sensor devices themselves, while paying little attention to the means to integrate this novel technology into the current enterprise infrastructure. We argue that facilitating this integration would encourage the adoption of sensor networks. Thus we present a scalable message broker for message-oriented middleware that is able to interact with any sensor network by providing a flexible and extensible communication subsystem. This message broker then provides the link to the messaging middleware used in the enterprise network. We describe the architecture of such a broker's communication subsystem and its implementation in Java&trade;. We present the performance of the broker, demonstrating that it scales to interconnect many sensor networks and is able to cope with potentially very large amounts of data from the sensors' readings. Finally, we present an overview of the sensor protocols we have developed, and how they are integrated into the broker, enabling for end-to-end interaction with external enterprise applications unaware of the sensor technology.
Automatic recognition of logical relations for English, Chinese and Japanese in the GLARF framework
Authors: Adam Meyers, Michiko Kosaka, Nianwen Xue, Heng Ji, Ang Sun, Shasha Liao, Wei Xu
Venue: Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions (2009)

We present GLARF, a framework for representing three linguistic levels and systems for generating this representation. We focus on a logical level, like LFG's F-structure, but compatible with Penn Treebanks. While less finegrained than typical semantic role labeling approaches, our logical structure has several advantages: (1) it includes all words in all sentences, regardless of part of speech or semantic domain; and (2) it is easier to produce accurately. Our systems achieve 90% for English/Japanese News and 74.5% for Chinese News -- these F-scores are nearly the same as those achieved for treebank-based parsing.
The Uprising: An Unauthorized Tour of the Populist Revolt Scaring Wall Street and Washington
Authors: David Sirota
Venue:  (2009)

An all-access pass to the populist insurrection brewing across the country. Job outsourcing. Slashed paychecks. A war without end, fatally mismanaged. Americans on both the Right and Left are tired of being disenfranchised by corrupt politicians and are organizing to change the status quo. In his invigorating new book, David Sirota investigates this uprising, taking us into the trenches where real change is happeningin the headquarters of the most powerful third party in America, at an ExxonMobil shareholder meeting, and on the quasi-military staging area of a vigilante force on the Mexican border. The Uprising is essential reading for anyone who wants to look beyond presidential politics at the new populism that is reshaping the American political landscape.
Study on Pattern Preparing System for Three-Level Loop Tufting Carpet
Authors: Chen Guangfeng, Zhang Yawei, Jin Zhilei, Xu Yang, Meng Zhuo
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

Three-level loop tufting machine provides great capability to jacquard carpet production, and also brings difficulties for the pattern design processing. To meet this requirement, this paper proposed a pattern preparing system for the tufting machine. Through the analysis of the basic pattern design requirements, the pattern preparing software structure was designed, in which core module includes pattern design and pattern conversion part. Pattern design part based on image processing accomplishes jacquard pattern computer aided design. Pattern conversion part transforms the design patterns into control pattern which is based on varied technical conditions. The proposed system was developed with the C++ language.
Lazy naive credal classifier
Authors: Giorgio Corani, Marco Zaffalon
Venue: Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data (2009)

We propose a local (or lazy) version of the naive credal classifier. The latter is an extension of naive Bayes to imprecise probability developed to issue reliable classifications despite small amounts of data, which may then be carrying highly uncertain information about a domain. Reliability is maintained because credal classifiers can issue set-valued classifications on instances that are particularly difficult to classify. We show by extensive experiments that the local classifier outperforms the original one, both in terms of accuracy of classification and because it leads to stronger conclusions (i.e., set-valued classifications made by fewer classes). By comparing the local credal classifier with a local version of naive Bayes, we also show that the former reliably deals with instances which are difficult to classify, unlike the local naive Bayes which leads to fragile classifications.
A basic study of ultrasonic shear wave elastography in tissue-mimicking phantoms
Authors: V. Rengaraju, A. F. F. da Silva, I. Sack, Ch. Kargel
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

Since many diseases cause changes in the mechanical properties of soft tissues, it is of interest to image their elasticity. Detection of tumors in early stages is challenging but paramount for the proper treatment of patients and thus to reduce the mortality rate. Elasticity imaging (elastography) has great potential to improve tumor diagnosis and is being developed and tested by several research groups with ultrasound and magnetic resonance imaging (MRI). As opposed to MRI, medical ultrasound is widely available, much more cost-effective and most of all a real-time imaging modality. In this paper we evaluate ultrasonic shear wave elastography, a dynamic approach to determine soft tissue properties. Our feasibility study using tissue-mimicking phantoms demonstrates that low frequency shear wave oscillation amplitudes in the micrometer range can be measured using commercial ultrasound scanners in combination with a particular signal processing method. Stiff tissue regions (tumors) show smaller shear wave amplitudes than the surrounding normal tissue. Not only can the examination time be reduced from about 10–20 minutes (MRI) to a few seconds, it may also soon be possible to detect certain cardiovascular dysfunctions in real-time using ultrasonic shear wave elastography.
A Novel Approach of Personal Identification Based on Single Knuckleprint Image
Authors: Rui Zhao, Kunlun Li, Ming Liu, Xue Sun
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

A novel approach which use single knuckleprint image only to implement personal identification is presented in this paper. Unlike most previous work, there is no need to collect a large amount of images to train the classifier. The identification process can be divided into the following stages: extracting the feature of the knuckleprint and matching the line feature. For the texture characteristic of the knuckleprint, we use a Self-defined convolution template as the gradient operator to carry out the edge detection and extract it’s line feature. Moreover, In order to solve the dislocation of the images between the matching images, a new method for line feature matching is proposed, which improved the correct identification rate at a large extent. The approach was tested on a database of 98 people (1,579 Knuckleprint images). The experimental results showed the effectiveness of the method is obviously.
Study of Dependencies in Executions of E-Contract Activities
Authors: K. Vidyasankar, P. Radha Krishna, Kamalakar Karlapalem
Venue: Proceedings of the 13th East European Conference on Advances in Databases and Information Systems (2009)

An e-contract is a contract modeled, specified, executed, controlled and monitored by a software system. A contract is a legal agreement involving parties, activities, clauses and payments. The goals of an e-contract include precise specification of the activities of the contract, mapping them into deployable workflows, and providing transactional support in their execution. Activities in a contract are generally complex and interdependent. They may be executed by different parties autonomously and in a loosely coupled fashion. They differ from database transactions in many ways: (i) Different successful executions are possible for an activity; (ii) Unsuccessful executions may be compensated or re-executed to get different results; (iii) Whether an execution is successful or not may not be known until after several subsequent activities are executed, and so it may be compensated and/or re-executed at different times relative to the execution of other activities; (iv) Compensation or re-execution of an activity may require compensation or re-execution of several other activities; etc. In this paper, we study the interdependencies between the executions of e-contract activities. This study will be helpful in monitoring behavioral conditions stated in an e-contracts during its execution.