ppxscal/embedding_network huggingface dataset:
Research on the Application of Industrial CT for Relics Image Reconstruction
Authors: Kai Zhang, Hong Bao, Min Zhou
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

The purpose of this paper is to visualizing the internal structure of historic relics by using the industrial computed-tomography (CT). The image reconstruction of CT scan data can be used to observe and analyze the antique inside that the eye has no way to distinguish without disruption. This paper have built the simulated testing model, produced the data of simulating projection, and accomplished the comparison of image reconstruction between of ART(SIRT) and FDK algorithm. After handling the real data of different materials, the experiment and analysis of CT image reconstruction have been carried out. This job has provided the effective technology support in the research of the heritage computed tomography scan platform. This paper also has provided the information for teaching and learning activities of cultural studies.
Optimal schedules for parallelizing anytime algorithms: the case of shared resources
Authors: Lev Finkelstein, Shaul Markovitch, Ehud Rivlin
Venue: Journal of Artificial Intelligence Research (2003)

The performance of anytime algorithms can be improved by simultaneously solving several instances of algorithm-problem pairs. These pairs may include different instances of a problem (such as starting from a different initial state), different algorithms (if several alternatives exist), or several runs of the same algorithm (for non-deterministic algorithms). In this paper we present a methodology for designing an optimal scheduling policy based on the statistical characteristics of the algorithms involved. We formally analyze the case where the processes share resources (a single-processor model), and provide an algorithm for optimal scheduling. We analyze, theoretically and empirically, the behavior of our scheduling algorithm for various distribution types. Finally, we present empirical results of applying our scheduling algorithm to the Latin Square problem.
Fault Feature Extraction Method of Time-Frequency Image Based on Fractal Dimension
Authors: Zhihua Hao, LiXin Tian
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

A fault feature extraction method of time-frequency image based on fractal dimension is put forward in this paper. Theoretical calculation formulas of fractal dimension are introduced and the calculation method about box-counting dimension based on image processing is analyzed. Based on this, the vibration signals measured from diesel engine in the stage of deflagration are researched with smooth slice Wigner higher order moment spectrums. Then the dimensions of fractal images which were obtained from the signal waves and the Wigner higher order moment spectrums are calculated by the fractal dimension calculation program. The result indicates that different wearing stages of piston-cylinder can be discriminated depending on feature parameters of fractal dimension because the fractal dimensions of images are apparently different.
A Two-Level Structure for Compressing Aligned Bitexts
Authors: Joaquín Adiego, Nieves R. Brisaboa, Miguel A. Martínez-Prieto, Felipe Sánchez-Martínez
Venue: Proceedings of the 16th International Symposium on String Processing and Information Retrieval (2009)

A bitext, or bilingual parallel corpus, consists of two texts, each one in a different language, that are mutual translations. Bitexts are very useful in linguistic engineering because they are used as source of knowledge for different purposes. In this paper we propose a strategy to efficiently compress and use bitexts, saving, not only space, but also processing time when exploiting them. Our strategy is based on a two-level structure for the vocabularies, and on the use of biwords, a pair of associated words, one from each language, as basic symbols to be encoded with an ETDC [2] compressor. The resulting compressed bitext needs around 20% of the space and allows more efficient implementations of the different types of searches and operations that linguistic engineerings need to perform on them. In this paper we discuss and provide results for compression, decompression, different types of searches, and bilingual snippets extraction.
iPhoto '09 For Dummies
Authors: Angelo Micheletti
Venue: For Dummies (2009)

iPhoto 09 is packed with cool photo-editing features, and iPhoto 09 For Dummies is your fast track to using every one. Youll learn to clean up and enhance your photos, print them or upload them to a sharing site online, create cool projects, protect and secure your pictures, and make photography more fun than ever. This full-color guide shows you how, and even helps you shoot future photos with an eye to iPhotos capabilities. Theres an easy exercise to get you started and plenty of beautiful full-color photos to show you the results you can achieve. Youll learn your way around the interface, whats new, and how to set preferences. Discover how to create a well-organized, maintainable archive so you can find photos Import and export photos from various sources, including card readers Manage any import problems Organize your collection using facial recognition and GPS technology Crop, rotate, and enhance your images Use a histogram and improve exposure, contrast, highlights, shadows, saturation, and more Set up a MobileMe gallery, send photos to Facebook or Flickr, make prints, and burn CDs Get tips for successfully e-mailing your pictures and for printing your photos at home Create photo greeting cards, calendars, or a travel book with maps that show where you took your pictures iPhoto 09 For Dummies even tells about cool add-ons and ideas for iPhoto. Learn to make all your photos the best they can be. 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
Learning Betting Tips from Users' Bet Selections
Authors: Erik Štrumbelj, Marko Robnik Šikonja, Igor Kononenko
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

In this paper we address the problem of using bet selections of a large number of mostly non-expert users to improve sports betting tips. A similarity based approach is used to describe individual users' strategies and we propose two different scoring functions to evaluate them. The information contained in users' bet selections improves on using only bookmaker odds. Even when only bookmaker odds are used, the approach gives results comparable to those of a regression-based forecasting model.
It's a contradiction---no, it's not: a case study using functional relations
Authors: Alan Ritter, Doug Downey, Stephen Soderland, Oren Etzioni
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Contradiction Detection (CD) in text is a difficult NLP task. We investigate CD over functions (e.g., BornIn(Person)=Place), and present a domain-independent algorithm that automatically discovers phrases denoting functions with high precision. Previous work on CD has investigated hand-chosen sentence pairs. In contrast, we automatically harvested from the Web pairs of sentences that appear contradictory, but were surprised to find that most pairs are in fact consistent. For example, "Mozart was born in Salzburg" does not contradict "Mozart was born in Austria" despite the functional nature of the phrase "was born in". We show that background knowledge about meronyms (e.g., Salzburg is in Austria), synonyms, functions, and more is essential for success in the CD task.
Exploring Children's Perceptions of the Robots
Authors: Yi-Chun Lin, Tzu-Chien Liu, Maiga Chang, Shiau-Ping Yeh
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

In order to introduce robots into education field appropriately, it is necessary to consider the children's perceptions of the robots. In this study, the researchers developed the questionnaire for exploring the children's general impressions of the robots, the roles of the robots in the classroom and the appearances of the robots. A hundred and sixty seven fifth-grade children took this questionnaire. The results show that most students have good impressions of the robots and positive attitude to see the robots in their classroom. Their responses also reveal that they might have over expectations of the robots. Besides, the results show that most of children like cartoon character-like robots and animal- like robots, because the robots are very cute.
Statistical Evaluation of Speech Features for Emotion Recognition
Authors: Theodoros Iliou, Christos-Nikolaos Anagnostopoulos
Venue: Proceedings of the 2009 Fourth International Conference on Digital Telecommunications (2009)

This paper presents an emotion recognition framework based on sound processing could significantly improve human computer interaction. One hundred thirty three (133) speech features obtained from sound processing of acting speech were tested in order to create a feature set sufficient to discriminate between seven emotions. Following statistical analysis in order to assess the significance of each speech feature, artificial neural networks were trained to classify emotions on the basis of a 35-input vector, which provide information about the prosody of the speaker over the entire sentence. Extra emphasis was given to assess the proposed 35-input vector in a speaker independent framework since test instances belong to different speakers from the training set. Several experiments were performed and the results are presented analytically. Considering the inherently difficulty of the problem, the proposed feature vector achieved promising results (51%) for speaker independent recognition in the seven emotion classes of Berlin Database.
ARM Assembly Language: Solutions Manual
Authors: William Hohl
Venue:  (2009)

Suitable for those with some background in digital logic and high-level programming, this work serves as a text for new programmers, as well as a reference for students and professionals. It focuses on what is needed to compile for ARM, details real assembly uses, and explores situations that programmers may ultimately encounter. 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
The Simulation Research of Non-parametric Regression for Short-Term Traffic Flow Forecasting
Authors: Xiao-li Zhang, Hua-pu Lu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

Short-term traffic flow forecasting play an important pole in urban traffic control and induction system. Non-Parametric Regression (NPR) is one perfect method for short-term traffic flow forecasting based on pattern recognition. At present time, the application research of NPR for short-term traffic flow forecasting is confined in small-scale fields and has less study of forecasting mechanism. This paper is trying to use the simulation measure to research the applicability of NPR in short-term traffic flow forecasting and study the forecasting principles by adjusting different system parameters. A typical road network is constructed as the study object in this paper. The forecasting problems of NPR are studied based on it. The data pre-processing of principal component analysis and cluster analysis are used for better forecasting results. Other network structures have only different simulation parameters with the presented network.
Confidentiality Simulation in a Simplified Database Model
Authors: Marn-Ling Shing, Chen-chi Shing, Kuo Lane Chen, Huei Lee
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

In an e-commerce environment, databases are accesses constantly. This paper looks into the confidentiality issues involved in a simplified database access. In a simplified secured database access model, there are two groups involved: privileged group and public group which they can access data with any distribution. In order to secure the confidentiality policy of the database, this paper shows how to simulate an Erlang distribution which is used in a proposed semi-Markov chains.
Technologies for the Social Semantic Desktop
Authors: Michael Sintek, Siegfried Handschuh, Simon Scerri, Ludger Elst
Venue: Reasoning Web. Semantic Technologies for Information Systems: 5th International Summer School 2009, Brixen-Bressanone, Italy, August 30 - September 4, 2009, Tutorial Lectures (2009)

The vision of the Social Semantic Desktop defines a user's personal information environment as a source and end-point of the Semantic Web: Knowledge workers comprehensively express their information and data with respect to their own conceptualizations. Semantic Web languages and protocols are used to formalize these conceptualizations and for coordinating local and global information access.A core challenge is to integrate existing legacy Desktop data into the Social Semantic Desktop. Semantic lifting is the process of capturing the semantics of various types of (semi-)structured data and/or non-semantic metadata and translating such data into Semantic Web conceptualizations.From the way the vision of the Social Semantic Desktop is being pursued in the NEPOMUK project, we identified several requirements and research questions with respect to knowledge representation. In addition to the general question of the expressivity needed in such a scenario, two main challenges come into focus: i) How can we cope with the heterogeneity of knowledge models and ontologies, esp. multiple knowledge modules with potentially different interpretations? ii) How can we support the tailoring of ontologies towards different needs in various exploiting applications?In this paper, we present semantic lifting as a means to create semantic metadata and the Nepomuk Representation Language (NRL) as a means to represent these metadata. NRL is an approach to these two aforementioned questions that is based on named graphs for the modularization aspect and a view concept for the tailoring of ontologies. This view concept turned out to be of additional value, as it also provides a mechanism to impose different semantics on the same syntactical structure.We furthermore present some of the ontologies that have been developed with the help of NRL in the NEPOMUK project to build the semantic foundations for the Social Semantic Desktop.
Knowledge Discovery on In Vitro Fertilization Clinical Data Using Particle Swarm Optimization
Authors: Chih-Chuan Chen, Chao-Chin Hsu, Yi-Chung Cheng, Sheng-Tun Li
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

In vitro fertilization (IVF) is a medically assisted reproduction technique (ART) for treating infertility. During IVF procedures, a female patient requires hormone treatment to control ovulation, oocytes are taken from the patient and fertilized in vitro, and after fertilization, one or usually more resulting embryos are transferred into the uterus. Although IVF is considered as a method of last resort for infertile couples, the success rate is still low, which can be only as high as 40% for women under age of 30. In this study, we build a predictive model which takes into account a patient’s physiology and the results of the stages of an IVF cycle, to assist obstetricians and gynecologists in increasing success rate of IVF. The predictive model is based on a knowledge discovering technique incorporated with particle swarm optimization (PSO), which is a competitive heuristic technique for solving optimization task. This study uses the database of IVF cycles developed by a women and infants clinic in Taiwan as the foundation. Arepertory grid is developed to help selecting attributes for the data mining technique. The results show that the proposed technique can exploit rules approved by the obstetrician/gynecologist and the assistant on both comprehensibility and justifiability.
Real-Time Backchannel Selection for ECAs According to User's Level of Interest
Authors: Etienne Sevin, Catherine Pelachaud
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

A great challenge that is to be faced in the design of virtual agents is the issue of credibility, not only in the agent's aspect but also in its behavior [1]. To be believable, the agent has to decide what to do next according to the internal and external variables of the agent. Besides others, we have to deal with the problem of action selection which can be resumed to choose the most appropriate action among all possible (conflicting) ones [2]. In our case, actions are backchannels. This work is part of the STREP EU SEMAINE project in which a real-time Embodied Conversational Agent (ECA) will be a Sensitive Artificial Listener (SAL) [3]. This project aims to build an autonomous talking agent able to exhibit autonomously appropriate verbal and non verbal behaviors in real-time when it plays the role of the listener in a conversation with a user.
Bringing Robustness to Patient Flow Management Through Optimized Patient Transports in Hospitals
Venue: Interfaces (2009)

Intrahospital transports are often required for diagnostic or therapeutic reasons. Depending on the hospital layout, transportation between nursing wards and service units is either provided by ambulances or by trained personnel who accompany patients on foot. In many large German hospitals, the patient transport service is poorly managed and lacks work-flow coordination. This contributes to higher hospital costs (e.g., because a patient is not delivered to the operating room on time) and to patient inconvenience (e.g., because of long waiting times). We designed a computer-based planning system, Opti-TRANS©, that supports all phases of the transportation flow, including travel booking, dispatching transport requests, and monitoring and reporting trips in real time. The methodology, which we developed to solve the underlying optimization problem---a dynamic dial-a-ride problem with hospital-specific constraints, draws on fast heuristic methods to ensure the efficient and timely provision of transports. We illustrate the strong impact of Opti-TRANS on the daily performance of the patient transportation service of a large German hospital. The major benefits of Opti-TRANS include streamlined transportation processes and work flow, significant savings, and improved patient satisfaction. Moreover, it has contributed to increased awareness among hospital staff of the importance of implementing efficient logistics practices.
Dependency parsing with dynamic Bayesian network
Authors: Virginia Savova, Leonid Peshkin
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Exact parsing with finite state automata is deemed in-apropriate because of the unbounded non-locality languages overwhelmingly exhibit. We propose a way to structure the parsing task in order to make it amenable to local classification methods. This allows us to build a Dynamic Bayesian Network which uncovers the syntactic dependency structure of English sentences. Experiments with the Wall Street Journal demonstrate that the model successfully learns from labeled data.
Mobile-Banking Adoption and Usage by Low-Literate, Low-Income Users in the Developing World
Authors: Indrani Medhi, Aishwarya Ratan, Kentaro Toyama
Venue: Proceedings of the 3rd International Conference on Internationalization, Design and Global Development: Held as Part of HCI International 2009 (2009)

Due to the increasing penetration of mobile phones even in poor communities, mobile-phone-enabled banking (m-banking) services are being increasingly targeted at the "unbanked" to bring formal financial services to the poor. Research in understanding actual usage and adoption by this target population, though, is sparse. There appear to be a number of issues which prevent low-income, low-literate populations from meaningfully adopting and using existing m-banking services. This paper examines variations across countries in adoption and usage of existing m-banking services by low-literate, low-income individuals and possible factors responsible for the same. It is observed that variations are along several parameters: household type, services adopted, pace of uptake, frequency of usage, and ease of use. Each of these observations is followed by a set of explanatory factors that mediate adoption and usage.
Study on Ensemble Classification Methods towards Spam Filtering
Authors: Jinlong Wang, Ke Gao, Yang Jiao, Gang Li
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

Recently, many scholars make use of fusion of filters to enhance the performance of spam filtering. In the past several years, a lot of effort has been devoted to different ensemble methods to achieve better performance. In reality, how to select appropriate ensemble methods towards spam filtering is an unsolved problem. In this paper, we investigate this problem through designing a framework to compare the performances among various ensemble methods. It is helpful for researchers to fight spam email more effectively in applied systems. The experimental results indicate that online based methods perform well on accuracy, while the off-line batch methods are evidently influenced by the size of data set. When a large data set is involved, the performance of off-line batch methods is not at par with online methods, and in the framework of online methods, the performance of parallel ensemble is better when using complex filters only.
A wizard-of-oz environment to study referring expression generation in a situated spoken dialogue task
Authors: Srinivasan Janarthanam, Oliver Lemon
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

We present a Wizard-of-Oz environment for data collection on Referring Expression Generation (REG) in a real situated spoken dialogue task. The collected data will be used to build user simulation models for reinforcement learning of referring expression generation strategies.