ppxscal/embedding_network huggingface dataset:
An application-aware approach to efficient power management in mobile devices
Authors: Ana Belen Lago, Iker Larizgoitia
Venue: Proceedings of the Fourth International ICST Conference on COMmunication System softWAre and middlewaRE (2009)

Reducing the energy consumed by mobile wireless devices to extend the lifetime of the batteries that power them is one of the major challenges in designing such systems. While this problem can be addressed at various levels (e.g. device, operating system, middleware, application), we think that it is possible to get a higher energy saving when considering the needs of the applications (application-aware). Our approach is centred on analyzing the behaviour of the applications more than the resources. In this paper, we present an application-aware framework which utilizes the needs of the applications and Dynamic Power Management (DPM) techniques focused on the wireless network card to control and reduce power consumption at runtime. We include a novel technique that increases the energy savings. We have also developed a simple prototype to test the viability of our idea. The experimental results show that the proposed approach achieves between 10% - 40% average reduction in the energy consumed by the wireless network interface.
k-link EST clustering
Authors: Lauren M. Bragg, Glenn Stone
Venue: Bioinformatics (2009)

Motivation: The clustering of expressed sequence tags (ESTs) is a crucial step in many sequence analysis studies that require a high level of redundancy. Chimeric sequences, while uncommon, can make achieving the optimal EST clustering a challenge. Single-linkage algorithms are particularly vulnerable to the effects of chimeras. To avoid chimera-facilitated erroneous merges, researchers using single-linkage algorithms are forced to use stringent sequence–similarity thresholds. Such thresholds reduce the sensitivity of the clustering algorithm. Results: We introduce the concept of k-link clustering for EST data. We evaluate how clustering error rates vary over a range of linkage thresholds. Using k-link, we show that Type II error decreases in response to increasing the number of shared ESTs (ie. links) required. We observe a base level of Type II error likely caused by the presence of unmasked low-complexity or repetitive sequence. We find that Type I error increases gradually with increased linkage. To minimize the Type I error introduced by increased linkage requirements, we propose an extension to k-link which modifies the required number of links with respect to the size of clusters being compared. Availability: The implementation of k-link is available under the terms of the GPL from http://www.bioinformatics.csiro.au/products.shtml. k-link is licensed under the GNU General Public License, and can be downloaded from http://www.bioinformatics.csiro.au/products.shtml. k-link is written in C++. Contact: lauren.bragg@csiro.au Supplementary information:Supplementary data are available at Bioinformatics online.
Towards empirical evaluation of affective tactical NLG
Authors: Ielka van der Sluis, Chris Mellish
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

One major aim of research in affective natural language generation is to be able to use language intelligently to induce effects on the emotions of the reader/ hearer. Although varying the content of generated language ("strategic" choices) might be expected to change the effect on emotions, it is not obvious that varying the form of the language ("tactical" choices) can do this. Indeed, previous experiments have been unable to show emotional effects of tactical variations. Building on what has been discovered in previous experiments, we present a new experiment which does demonstrate such effects. This represents an important step towards the empirical evaluation of affective NLG systems.
A New Linguistic-Perceptual Event Model for Spatio-Temporal Event Detection and Personalized Retrieval of Sports Video
Authors: Minh-Son Dao, Sharma Ishan Nath, Noboru Babaguichi
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

This paper proposes a new linguistic-perceptual event model tailoring to spatio-temporal event detection and conceptual-visual personalized retrieval of sports video sequences. The major contributions of the proposed model are hierarchical structure, independence between linguistic and perceptual part, and ability of capturing temporal information of sports events. Thanks to these advanced contributions, it is very easy to upgrade model events from simple to complex levels either by self-studying from inner knowledge or by being taught from plug-in additional knowledge. Thus, the proposed model not only can work well in unwell structured environments but also is able to adapt itself to new domains without the need (or with a few modification) for external re-programming, re-configuring and re-adjusting. Thorough experimental results demonstrate that events are modeled and detected with high accuracy and automation, and users' expectation of personalized retrieval is highly satisfied.
High performance and low cost architecture for H.264/AVC CAVLD targeting HDTV
Authors: Thaísa Silva, Fabio Pereira, Altamiro Susin, Sergio Bampi, Luciano Agostini
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

This work presents a high throughput and low cost architecture for the Context Adaptive Variable Length Decoder (CAVLD) of the H.264/AVC video coding standard. Usually, a large number of memory bits and memory accesses are required to decode the CAVLD in H.264/AVC since a large number of syntax elements are decoded based on look-up tables. To solve this problem, we propose an efficient decoding of syntax elements through the use of tree structures. Due to the difficulty to parallelize operations with variable length codes, we have proposed a few optimizations aiming to improve performance, and these optimizations are presented in this paper. The designed architecture was described in VHDL and synthesized to TSMC 0.18&mu;m CMOS standard-cells technology. The obtained results show that this solution reached the necessary throughput to decode HDTV videos (1920x1080 pixels) in real-time (30fps).
Speckled Tango Dancers: Real-Time Motion Capture of Two-Body Interactions Using On-body Wireless Sensor Networks
Authors: D. K. Arvind, Aris Valtazanos
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

This paper describes the application of a fully wireless network of on-body inertial/magnetic sensors for the 3-D motion capture and real-time analysis of Tango dancers.Accomplished Tango dancers exhibit both individual flair and good co-ordination with their partners. Features have been identified which differentiate the better dancers, such as chest-bend angle, synchronisation between the chest and foot movements, and chest movement co-ordination, which reflect the performance of both the individual and of the partnership. These features have been analysed on live data for characterisingthe dancers’ performances.The aim in the future is to design a dance tutoring tool which will analyse the sensor data and provide feedback for improvement.
Spatial Data Model for Visualization System of GIS Based Urban Pipe Network
Authors: Juan Yang, Hao Lin, Yupeng Xiao, Xiaoting Fu, Liutong Xu
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Since planar graphics can not meet the needs of precisely reflecting real spatial relationship between pipelines, it is necessary to build a 3D visualization system of urban pipe network. 3D spatial data model is the basis of data representation and spatial visualization. Based on the analysis of the features of urban pipe network and the requirements of the 3D model, a spatial data model for Urban Pipe Network Visualization System (UPNVS) is designed and organized by spatial metadata. The advantage of the spatial metadata is discussed in the paper. The application of the model in a real project shows that it is effective.
Web 2.0 Architectures: What entrepreneurs and information architects need to know, 1st edition
Authors: James Governor, Dion Hinchcliffe, Duane Nickull
Venue:  (2009)

Web 2.0 is more pervasive than ever, with business analysts and technologists struggling to comprehend the opportunity it represents. But what exactly is Web 2.0 -- a marketing term or technical reality? This fascinating book finally puts substance behind the phenomenon by identifying the core patterns of Web 2.0, and by introducing an abstract model and reference architecture to help you take advantage of them. In Web 2.0 Architectures, authors Duane Nickull, Dion Hinchcliffe, and James Governor -- who have 40 years of combined experience with technical specifications and industry trends -- examine what makes successful Web 2.0 services such as Google AdSense, Flickr, BitTorrent, MySpace, Facebook, and Wikipedia tick. The result is a base of knowledge that developers, business people, futurists, and entrepreneurs can understand and use as a source of ideas and inspiration. This book reveals: A Model for Web 2.0 -- An in-depth look at how the classic Client-Server model has evolved into a more detailed Web 2.0 model. Web 2.0 Reference Architecture -- A generic component view that helps decision-makers recognize basic patterns in existing Web 2.0 applications-patterns that can be repurposed for other commercial ventures. Specific Patterns of Web 2.0 -- How Service Oriented Architecture (SOA), Software as a Service pattern (SaaS), Participation-Collaboration Pattern, AJAX, Mashups, Rich User Experience (a.k.a. RIA), Collaborative Tagging Systems (Folksonomy), and more can be used in your technology business. In true Web 2.0 fashion, Nickull, Hinchcliffe, and Governor will present the reference architecture and patterns on their companion website so that people in the industry can augment it and continue the discussion.
Data Fitting by Quadratic Splines
Authors: Fenghua Guo
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

In this paper the problem of data fitting using quadratic spline is addressed. An efficient algorithm is presented. Given a set of ordered planar points, the algorithm divides this set of points into subsets, while the data points in each subset are collinear within the given tolerance. The data points in each subset are fitted by a curve segment and all data points are fitted by a C1 quadratic spline curve. The algorithm is simple and reliable, decreases the number of fitting curve segments and maintains the approximating accuracy. This algorithm is tested and can be applied to reverse engineering and image curves fitting.
Real-time guidewire simulation in complex vascular models
Authors: Vincent Luboz, Rafal Blazewski, Derek Gould, Fernando Bello
Venue: The Visual Computer: International Journal of Computer Graphics (2009)

The base of all training in interventional radiology aims at the development of the core skills in manipulating the instruments. Computer simulators are emerging to help in this task. This paper extends our previous framework with more realistic instrument behaviour and more complex vascular models. The instrument is modelled as a hybrid mass&#x2013;spring particle system while the vasculature is a triangulated surface mesh segmented from patient data sets. A specially designed commercial haptic device allows the trainee to use real instruments to guide the simulation through the vasculature selected from a database of 23 different patients. A new collision detection algorithm allows an efficient computation of the contacts, therefore leaving more time to deal with the collision response for a realistic simulation in real time. The behaviour of our simulated instruments has been visually compared with the real ones and assessed by experienced interventional radiologists. Preliminary results show close correlations and a realistic behaviour.
Acceptable consistency analysis of interval reciprocal comparison matrices
Authors: Fang Liu
Venue: Fuzzy Sets and Systems (2009)

When a decision maker expresses his/her opinions by means of an interval reciprocal comparison matrix, the study of consistency becomes a very important aspect in decision making in order to avoid a misleading solution. In the present paper, an acceptably consistent interval reciprocal comparison matrix is defined, which can be reduced to an acceptably consistent crisp reciprocal comparison matrix when the intervals become exact numbers. An interval reciprocal comparison matrix with unacceptable consistency can be easily adjusted such that the revised matrix possesses acceptable consistency. Utilizing a convex combination method, a family of crisp reciprocal comparison matrices with acceptable consistency can be obtained, whose weights are further found to exhibit a style of convex combination, and aggregated to obtain interval weights from an acceptably consistent interval reciprocal comparison matrix. A novel, simple yet effective formula of possibility degree is presented to rank interval weights. Numerical results are calculated to show the quality and quantity of the proposed approaches and compare with other existing procedures.
Sussx: WSD using automatically acquired predominant senses
Authors: Rob Koeling, Diana McCarthy
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

We introduced a method for discovering the predominant sense of words automatically using raw (unlabelled) text in (McCarthy et al., 2004) and participated with this system in Senseval3. Since then, we worked on further developing ideas to improve upon the base method. In the current paper we target two areas where we believe there is potential for improvement. In the first one we address the finegrained structure of WordNet's (wn) sense inventory (i.e. the topic of the task in this particular track). The second issue we address here, deals with topic domain specilisation of the base method.
The Needles-in-Haystack Problem
Authors: Katherine Moreland, Klaus Truemper
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

We consider a new problem of detecting members of a rare class of data, the needles, which have been hidden in a set of records, the haystack. The only information regarding the characterization of the rare class is a single instance of a needle. It is assumed that members of the needle class are similar to each other according to an unknown needle characterization. The goal is to find the needle records hidden in the haystack. This paper describes an algorithm for that task and applies it to several example cases.
Full Description Persona vs. Trait List Persona in the Persona-Based sHEM Approach
Authors: Masaaki Kurosu
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

Instead of the usual persona method (full description persona), a new type of persona (trait list persona) was proposed for the purpose of covering the wide variety of possible users. These two persona methods were then used to anticipate problems that might occur by applying sHEM (structured heuristic evaluation method) that is one of the inspection methods. In other words, it was not necessary to create the full descriptive scenario but just the possible lists of problems that are similar to the pMS (problem micro scenario) of micro scenario method were described.
Multiword expressions as dependency subgraphs
Authors: Ralph Debusmann
Venue: Proceedings of the Workshop on Multiword Expressions: Integrating Processing (2004)

We propose to model multiword expressions as dependency subgraphs, and realize this idea in the grammar formalism of Extensible Dependency Grammar (XDG). We extend XDG to lexicalize dependency subgraphs, and show how to compile them into simple lexical entries, amenable to parsing and generation with the existing XDG constraint solver.
Extracting phoneme pronunciation information from corpora
Authors: Ian Thomas, Ingrid Zukerman, Bhavani Raskutti
Venue: Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning (1998)

We present a procedure that determines a set of phonemes possibly intended by a speaker from a recognized or uttered phone. This information will be used to allow a speech recognizer to take pronunciation into account or to consider input from a noisy source during lexical access. We investigate the hypothesis that different pronunciations of a phone occur within groups of sounds physically produced the same way, and use the Minimum Message Length principle to consider the effect of a phoneme's context on its pronunciation.
Defeating Back Pain at the Workplace: Results of the "Healthy Back" Program
Authors: Christian Schwennen, Bernhard Zimolong
Venue: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International 2009 (2009)

A holistic occupational health management system was implemented at the German tax administration. It integrates a multi-component health program that focuses on back pain prevention. The present study reports results from the evaluation of the program. It consists of a health screening (N =1043) which measured 13 risk factors followed by tailored interventions. One half of the participants exhibit moderate to high risk for future back pain. Participation-rate of the program is 48.46%. Results reveal a significant increase in physical activity. Results of the pre-post-test evaluation show moderate changes in the psychological variables, except for a decrease in catastrophising. In addition, a substantial decrease in back pain frequency, -intensity and impairment through back pain could be observed. The results of the interventions are discussed with regard to participation issues of work site health programs.
Road Surface Condition Recognition Method Based on Color Models
Authors: Li Hong, Lin Jun, Feng Yanhui
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

A computer vision technique has been applied to analyze and research road surface meteorology. The original color data in HIS and RGB models has constituted feature vectors. Robust technique has been used to remove outliers before image process. And a BP neural network has been employed to identify the images collected from road surface in four kinds of states （namely, covered by dry asphalt, water, ice and snow）.The result of experiments shows that the means is effective.
The Path Choice to Minimize the Project Risk Based on the Possible Degree
Authors: Zhou Qihai, Sun Xiezhi, Li Zhongjun, Wang Jing, Han Zai-xing, Li Yan, Xia Yuanyuan
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

With the development of science and technology, the competition of situation in the market has become more and more fierce. The risk is everywhere. How to reduce risk, avoid risk, minimize risk of the project, is the urgent business, and in the current complicated situation, Cobb-Douglas production function as a mathematical model of the economy, because of its variable value of uncertainty, the economic model can not accurately describe the production of input-output relationship. This paper makes quantitative analysis and scientific choice based on multi-attribute decision-making of the possible degree approach to the feasibility of the path of project in business from the three factors (labor input, capital input and the technical level) which impact the project risk of enterprise, and consequently achieve the enterprise's risk minimization.
Analysis on Characteristic of the Rural Population Trip
Authors: Feng Zhongxiang, Liu Haoxue, Zhao Jianyou
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

To study the trip rule of rural population based on the modern economic can provide scientific foundation for government to formulate the relevant policies and plans. On the basis of the rural population of Shaanxi Province, this paper utilizes trip questionnaires to conduct an actual investigation into the trip condition of 1700 families, 7253 persons altogether, in order to sum up trip times, trip distance, trip mode and trip time distribution. In addition, it analyses the correlative factors which affect the trip of rural population. The result indicates that daily average trip times of the rural population is 0.07 times per person; the trip distance in the range of 8km accounts for about 75%, and Walk and bicycle-based trip mode, a small quantity of rural people travelled by motor and bus. Meanwhile, it’s proved that daily trip can be divided into three intervals, while the three corresponding trip number of rural population has shown decreasing tendency in sequence. Moreover, busy farming seasons and traditional festivals have deep effect on the distribution of trip months in the whole year. Finally, it verifies that trip times of the rural population is highly related to local economic level and geographical environment, also the layout of towns and villages is involved in the trip distances.
Transforming between propositions and features: bridging the gap
Authors: Daniel T. Halstead, Kenneth D. Forbus
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

It is notoriously difficult to simultaneously deal with both probabilistic and structural representations in A.I., particularly because probability necessitates a uniform representation of the training examples. In this paper, we show how to build fully-specified probabilistic models from arbitrary propositional case descriptions about terrorist activities. Our method facilitates both reasoning and learning. Our solution is to use structural analogy to build probabilistic generalizations about those cases. We use these generalizations as a framework for mapping the structural representations, which are well-suited for reasoning, into features, which are well-suited for learning, and back again. Finally, we demonstrate how probabilistic generalizations are an excellent bridge for joining reasoning and learning by using them to perform a traditional machine learning technique, Bayesian network modeling, over arbitrarily high order structural data about terrorist actions, and further, we discuss how this might be used to facilitate automatic knowledge acquisition.