ppxscal/embedding_network huggingface dataset:
Vision Based Obstacle Recognition Approach of a Power Line Inspection Robot
Authors: Qi Zuo, Zhi Xie, Zijian Guo
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

This paper introduces the research and application situations of the power transmission line inspection robot. It describes the architecture of two–arm rotary mechanism robot and the configuration of control system. The emphasis of this paper is placed on the algorithm of object recognition for those structure-restrained obstacles such as suspending clamps, counterweights, insulators and so on. The experiments of laboratory tests and field applications show that the proposed image recognition approach can achieve accurate results with less memory and computation cost.
Microsoft Office 2007: Illustrated Brief Premium Video Edition, 1st edition
Authors: Marjorie S. Hunt, Barbara Waxer
Venue:  (2009)

Give your students a comprehensive, hands-on, and engaging learning experience with the MICROSOFT OFFICE 2007-ILLUSTRATED BRIEF PREMIUM VIDEO EDITION. This Premium Video Edition includes a Video Companion containing approximately 100 videos each based on a two-page lesson in the book, 8 Capstone Projects and SAM Projects instruction files to help Bring Learning To Life! For both the computer "rookies" and the computer "hotshots" MICROSOFT OFFICE 2007-ILLUSTRATED BRIEF PREMIUM VIDEO EDITION appeals to all the learners in your classroom, covering the essential information that students need to know now. Our signature two-page spread design has been updated and refreshed to take full advantage of the new features of the Office 2007 software. This practical, easy-to-navigate book provides students with the essential knowledge they need to succeed in both the classroom and beyond.
Supporting Aphasics for Capturing, Organizing and Sharing Personal Experiences
Authors: Abdullah Al Mahmud
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

When a person, due to brain injury or another disease, suffers in his or her ability to speak, it becomes inherently cumbersome to share needs, emotions, and experiences through personal stories and social interaction. This paper describes the aim and progress of the author's dissertation, which focuses on designing a support system to share daily experiences for people suffering from expressive aphasia.
A custom collaboration service system for idea management of mobile phone design
Authors: Wei-Feng Tung, Soe-Tsyr Yuan, Je-Ren Tsai
Venue: Human Factors in Ergonomics Manufacturing (2009)

Customized collaborative service (CCS) systems are defined as the e-services transforming a business process into a collaborative service model and aiming to facilitate interactions with customers and assist the providers in dealing with collaborative strategies and activities. The demand for such services has grown rapidly in a shift of people out of the manufacturing mindset into the service-dominant mindset. For example, the mobile-phone market now tends to customization rather than commoditization, and customer-driven design strategies increasingly substitute for technology-driven design strategies. This trend accordingly urges the mobile-phone companies to center on a customer-centric idea management process to assure customer idea originality but also sustain the process feasibility for realistic product design. However, a method to engineer such CCS systems has not been addressed. This article presents a prototype system named iMobileDesign to exemplify a CCS system. We present a new methodology to engineer this CCS system aiming to achieve semiautomated value coproduction with productivity and satisfaction. This method comprises two parts: simple service machine (SSM) and intelligent service machine (ISM). Usage of SSM and ISM would lead to the formation of analysis and design of the CCS system that joins the service provider efforts with their customers for ensuring a customer-centric idea management process. &copy; 2009 Wiley Periodicals, Inc.
Markov decision process applied to the control of hospital elective admissions
Authors: Luiz Guilherme Nadal Nunes, Solon Veníncio de Carvalho, Rita de Cássia Meneses Rodrigues
Venue: Artificial Intelligence in Medicine (2009)

Objective: To present a decision model for elective (non-emergency) patient admissions control for distinct specialties on a periodic basis. The purpose of controlling patient admissions is to promote a more efficient utilization of hospital resources, thereby preventing idleness or excessive use of these resources, while considering their relative importance. Methods: The patient admission control is modeled as a Markov decision process. A hypothetical prototype is implemented, applying the value iteration algorithm. Results: The model is able to generate an optimal admission control policy that maintains resource consumption close to the desired levels of utilization, while optimizing the established deviation costs. Conclusion: This is a complex model due to its stochastic dynamic and dimensionality. The model has great potential for application, and requires the development of customized solution methods.
Comparing data mining methods with logistic regression in childhood obesity prediction
Authors: Shaoyan Zhang, Christos Tjortjis, Xiaojun Zeng, Hong Qiao, Iain Buchan, John Keane
Venue: Information Systems Frontiers (2009)

The epidemiological question of concern here is "can young children at risk of obesity be identified from their early growth records?" Pilot work using logistic regression to predict overweight and obese children demonstrated relatively limited success. Hence we investigate the incorporation of non-linear interactions to help improve accuracy of prediction; by comparing the result of logistic regression with those of six mature data mining techniques.The contributions of this paper are as follows: a) a comparison of logistic regression with six data mining techniques: specifically, for the prediction of overweight and obese children at 3 years using data recorded at birth, 6 weeks, 8 months and 2 years respectively; b) improved accuracy of prediction: prediction at 8 months accuracy is improved very slightly, in this case by using neural networks, whereas for prediction at 2 years obtained accuracy is improved by over 10%, in this case by using Bayesian methods. It has also been shown that incorporation of non-linear interactions could be important in epidemiological prediction, and that data mining techniques are becoming sufficiently well established to offer the medical research community a valid alternative to logistic regression.
Pro ASP.NET Extensibility
Authors: Joerg Krause
Venue:  (2009)

ASP.NETs new model for supporting language extensibility is intriguing to developers everywhere. With support for traditional, statically compiled languages like C# as well as dynamic languages like Python, ASP.NET now has a natural ability to support languages that developers want to work with, not ones they are forced to use. ASP.NET is quickly becoming an attractive place for todays dynamic languages. Pro ASP.NET Extensibility gives readers an indepth insight in the new language model within ASP.NET, going beyond the introductory treatment of the topic available elsewhere, full of practical tips and tricks from an experienced developer. Learn about the extensibility and runtime models available with both .NET 3.5 and 4.0, Windows Server 2003 and 2008, and Internet Information Services (IIS) 6.0 and 7.0. The book explains not only how things work but also why. Using Joerg Krauses experienced advice and sound tricks, youll be able to go further with your very own language projects and transform your .NET development on your own termsmade possible with ASP.NETs popular extensibility model. Discover how ASP.NET is extensible in .NET 3.5 and 4.0. Look indepth into the internals of ASP.NET page processing. Customize the behavior of the ASP.NET engine. What youll learn Understand .NET Frameworks general and ASP.NETs particular extensibility features. Extend, replace, or modify the default behavior of almost all basic page processing features. See how the runtime models internal processing works. Learn tips and tricks for optimizing your applications to run with new dynamic language support. Explore IronPython and the DLR. Get a look toward to the future, with advice on point for .NET 4.0 in each chapter Who is this book for? This book is for experienced ASP.NET developers who want to get the most out of ASP.NET and learn how to program reallife applications. Its also for beginners who want to know whats possible with ASP.NET. About the Apress Pro Series The Apress Pro series books are practical, professional tutorials to keep you on and moving up the professional ladder. You have gotten the job, now you need to hone your skills in these tough competitive times. The Apress Pro series expands your skills and expertise in exactly the areas you need. Master the content of a Pro book, and you will always be able to get the job done in a professional development project. Written by experts in their field, Pro series books from Apress give you the hardwon solutions to problems you will face in your professional programming career.
A high accuracy method for semi-supervised information extraction
Authors: Stephen Tratz, Antonio Sanfilippo
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)

Customization to specific domains of discourse and/or user requirements is one of the greatest challenges for today's Information Extraction (IE) systems. While demonstrably effective, both rule-based and supervised machine learning approaches to IE customization pose too high a burden on the user. Semi-supervised learning approaches may in principle offer a more resource effective solution but are still insufficiently accurate to grant realistic application. We demonstrate that this limitation can be overcome by integrating fully-supervised learning techniques within a semi-supervised IE approach, without increasing resource requirements.
Putting Semantics into WordNet's "Morphosemantic" Links
Authors: Christiane Fellbaum, Anne Osherson, Peter E. Clark
Venue: Human Language Technology. Challenges of the Information Society: Third Language and Technology Conference, LTC 2007, Poznan, Poland, October 5-7, 2007, Revised Selected Papers (2009)

To add to WordNet's contents, and specifically to aid automatic reasoning with WordNet, we classify and label the current relations among derivationally and semantically related noun-verb pairs. Manual inspection of thousands of pairs shows that there is no one-to-one mapping of form and meaning for derivational affixes, which exhibit far less regularity than expected. We determine a set of semantic relations found across a number of morphologically defined noun-verb pair classes.
Data Mining of Image Segments Data with Reduced Neurofuzzy System
Authors: Deok Hee Nam, Edward Asikele
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

The target detection from raw images is a primary task in the image processing. Simultaneously, in order to perform the target detection in the image processing, a large number of variables or factors including unnecessary factors may be involved. This paper presents the pattern recognition through the image scaling based upon the characteristics of various images using the reduced dimension from the original characteristic dimension of the images. Using the less number of dimensions comparing to the original characteristic dimensions, the processing procedures can be simplified and able to overcome the restrictions of the systematic problems. To estimate the performance of the system, neurofuzzy systems with multivariate analysis including factor analysis, principal component analysis, and Fuzzy C-means clustering analysis, are applied. Using the proposed algorithm, the analyses of various image data can be compared.
What Do We Know about Agile Software Development?
Authors: Tore Dyba, Torgeir Dingsoyr
Venue: IEEE Software (2009)

From 1,996 studies available in the agile software development literature, the authors identified 36 research studies of acceptable rigor, credibility, and relevance to include in a systematic review of empirical evidence for agile development's benefits and limitations. The review results suggest that despite some limitations, agile development can improve job satisfaction, project productivity, and customer satisfaction.
SVR-Based Jitter Reduction for Markerless Augmented Reality
Authors: Samuele Salti, Luigi Stefano
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

The ability to augment a video stream with consistent virtual contents is an attractive Computer Vision application. The first Augmented Reality (AR) proposals required the scene to be endowed with special markers. Recently, thanks to the developments in the field of natural invariant local features, similar results have been achieved in a markerless scenario. The computer vision community is now equipped with a set of relatively standard techniques to solve the underlying markerless camera pose estimation problem, at least for planar textured reference objects. The majority of proposals, however, does not exploit temporal consistency across frames in order to reduce some disturbing effects of per-frame estimation, namely visualization of short spurious estimations and jitter. We proposes a new method based on Support Vector Regression to mitigate these undesired effects while preserving the ability to work in real-time. Our proposal can be used as a post processing step independent of the chosen pose estimation method, thus providing an effective and easily integrable building block for AR applications.
Gossip Galore: a self-learning agent for exchanging pop trivia
Authors: Xiwen Cheng, Peter Adolphs, Feiyu Xu, Hans Uszkoreit, Hong Li
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations Session (2009)

This paper describes a self-learning software agent who collects and learns knowledge from the web and also exchanges her knowledge via dialogues with the users. The agent is built on top of information extraction, web mining, question answering and dialogue system technologies, and users can freely formulate their questions within the gossip domain and obtain the answers in multiple ways: textual response, graph-based visualization of the related concepts and speech output.
Multi-class Binary Symbol Classification with Circular Blurred Shape Models
Authors: Sergio Escalera, Alicia Fornés, Oriol Pujol, Petia Radeva
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we present the Circular Blurred Shape Model descriptor. This descriptor encodes the arrangement information of object parts in a correlogram structure. A prior blurring degree defines the level of distortion allowed to the symbol. Moreover, we learn the new feature space using a set of Adaboost classifiers, which are combined in the Error-Correcting Output Codes framework to deal with the multi-class categorization problem. The presented work has been validated over different multi-class data sets, and compared to the state-of-the-art descriptors, showing significant performance improvements.
Non-cancellation multistage kurtosis maximization with prewhitening for blind source separation
Authors: Xiang Chen, Chong-Yung Chi, Tsung-Hui Chang, Chon-Wa Wong
Venue: EURASIP Journal on Advances in Signal Processing (2009)

Chi et al. recently proposed two effective non-cancellation multistage (NCMS) blind source separation algorithms, one using the turbo source extraction algorithm (TSEA), called the NCMS-TSEA, and the other using the fast kurtosis maximization algorithm (FKMA), called the NCMS-FKMA. Their computational complexity and performance heavily depend on the dimension of multisensor data, that is, number of sensors. This paper proposes the inclusion of the prewhitening processing in the NCMS-TSEA and NCMS-FKMA prior to source extraction. We come up with four improved algorithms, referred to as the PNCMS-TSEA, the PNCMS-FKMA, the PNCMS-TSEA(p), and the PNCMS-FKMA(p). Compared with the existing NCMS-TSEA and NCMS-FKMA, the former two algorithms perform with significant computational complexity reduction and some performance improvements. The latter two algorithms are generalized counterparts of the former two algorithms with the single source extraction module replaced by a bank of source extraction modules in parallel at each stage. In spite of the same performance of PNCMS-TSEA and PNCMS-TSEA(p) (PNCMS-FKMA and PNCMS-FKMA(p)), the merit of this parallel source extraction structure lies in much shorter processing latency making the PNCMS-TSEA(p) and PNCMS-FKMA(p) well suitable for software and hardware implementations. Some simulation results are presented to verify the efficacy and computational efficiency of the proposed algorithms.
A Solution for TSP Based on Artificial Fish Algorithm
Authors: Wang Jian-ping, Hu Meng-jie
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

TSP is well-known issue in the field of mathematics. With the increasing calculation nodes, the convergence degree and computing difficulty of TSP will increase enormously. Artificial fish is an optimize algorithm based on biology model putting forward at present. We describe the relative knowledge of artificial fish algorithm, put forward artificial fish algorithm model for TSP, then make the qualitative analysis of the basic steps for simulating TSP.
Nanotechnology Research Collection 2009/2010: Online Book Edition
Authors: James N. Ling
Venue:  (2009)

This extraordinary collection presents the entire contents of 15 recent books on nanotechnology. Nanotechnology, refers to a field whose theme is the control of matter on an atomic and molecular scale. Generally nanotechnology deals with structures of the size 100 nanometres or smaller, and involves developing materials or devices within that size. Nanotechnology is extremely diverse, ranging from novel extensions of conventional device physics, to completely new approaches based upon molecular self-assembly, to developing new materials with dimensions on the nanoscale, even to speculation on whether we can directly control matter on the atomic scale. There has been much debate on the future of implications of nanotechnology. Nanotechnology has the potential to create many new materials and devices with wide-ranging applications, such as in medicine, electronics, and energy production. On the other hand, nanotechnology raises many of the same issues as with any introduction of new technology, including concerns about the toxicity and environmental impact of nanomaterials, and their potential effects on global economics, as well as speculation about various doomsday scenarios. These concerns have led to a debate among advocacy groups and governments on whether special regulation of nanotechnology is warranted. 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
An Ontology Enhanced Development Kit for Full Text Search
Authors: Su Jian, Weng Wenyong, Wang Zebing
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

An ontology enhanced development kit for full text search is discussed in this paper. The development kit consists of a few software modules. All of these modules constitute a three-layer architecture. The full text layer implements the methods for full text index and search; the ontology layer implements the methods for concept definition and ontology maintenance; the user layer provides the programming APIs and config tools for programmers. This development kit uses two widely-used development kits (i.e., Apache Lucene and Jena) as its foundation. Apache Lucene provides the basic techniques for full text index and search, while Jena provides the basic ontology techniques. This development kit will be easy to use since the underlying details of implementation are encapsulated, and the performance of full text search will be improved since the ontology techniques are used to fill the gap between the concepts and the words.
Hierarchical Collectives in MPICH2
Authors: Hao Zhu, David Goodell, William Gropp, Rajeev Thakur
Venue: Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2009)

Most parallel systems on which MPI is used are now hierarchical, such as systems with SMP nodes. Many papers have shown algorithms that exploit shared memory to optimize collective operations to good effect. But how much of the performance benefit comes from tailoring the algorithm to the hierarchical topology of the system? We describe an implementation of many of the MPI collectives based entirely on message-passing primitives that exploits the two-level hierarchy. Our results show that exploiting shared memory directly usually gives small additional benefit and suggests design approaches for where the benefit is large.
Study and Application of Agent in Personalized Tutoring System
Authors: Zhang Xiao-Bo, Liu Guang-Qi
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

The preferences of students in network learning are more disperse than that in traditional campus education. It has brought the personalized demand to teaching and tutoring system. A personalized tutoring system is important for effect of the network teaching and for knowledge science. For the existing network tutoring systems lack in the method and tactics of understanding user’s personalized needs in depth, a personalized tutoring system prototype based on Agent is given. By means of neural network technology, the system can discover user preferences at large, and realize aim of the personalized teaching.