ppxscal/embedding_network huggingface dataset:
Environmental Pollution and Endogenous Growth: Models and Evidence from China
Authors: Haibin Deng, Jing Huang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

A simple new classical growth model is developed to analyze the relationship between economic growth and environmental pollution, which proves the existence of the sustained growth path. This model is then endogenized to study the interaction among environmental pollution, human capital and economic growth in the long run. The similar growth path is shown and potent influences of different variables on the sustained growth are examined along the path. To bring the economy onto the sustained growth trajectory, we ought to increase human capital, implement stricter environmental standard, persist in the concept of sustained growth, build up environmental protection consciousness and improve green production technology. On the background of theoretical analysis, a simultaneous equation model is formed to empirically investigate the facts in China. The results show that China’s environment is being worsened with the rapid growth of economy. The implication is obvious. To achieve sustainable development, the Chinese government has no choice but to transform the growth pattern, to improve the industrial structure, to popularize clean technology, to reinforce pollution abatement.
Servo Follow-up System Controlled by CMAC ANN
Authors: Tao Zhang, Jingping Jiang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

Basing on the experiment of PMSM as an object, the paper applies the learning control algorithm to control the servo follow-up system. The characteristic analysis and simulation computations demonstrate that the project can apparently improve the velocity and accuracy of the tracking response to the servo follow-up system.
NLP and the humanities: the revival of an old liaison
Authors: Franciska de Jong
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

This paper present an overview of some emerging trends in the application of NLP in the domain of the so-called Digital Humanities and discusses the role and nature of metadata, the annotation layer that is so characteristic of documents that play a role in the scholarly practises of the humanities. It is explained how metadata are the key to the added value of techniques such as text and link mining, and an outline is given of what measures could be taken to increase the chances for a bright future for the old ties between NLP and the humanities. There is no data like metadata!
Working in IT
Authors: Rob England
Venue:  (2009)

Here you will find ideas and inspiration to think about your own career and the careers of those who work for you, and to make a difference in both. Rob England spent a lot of time developing and delivering professional development training for software consultants. He conceived, designed, developed and delivered training to over 80 staff. For some people it was life-changing. He is passionate about IT professionalism, IT career development, work-life balance, and saving geeks from themselves - and it is all in this book. 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
Classifying Time Series Data: A Nonparametric Approach
Authors: Juan Manuel Vilar, José Antonio Vilar, Sonia Pértega
Venue: Journal of Classification (2009)

A general nonparametric approach to identify similarities in a set of simultaneously observed time series is proposed. The trends are estimated via local polynomial regression and classified according to standard clustering procedures. The equality of the trends is checked using several nonparametric test statistics whose asymptotic distributions are approximated by a bootstrap procedure. Once the estimated trends are removed from the model, the residual series are grouped by means of a nonparametric cluster method specifically designed for time series. Such a method is based on a disparity measure between local linear smoothers of the spectra of the series. The performance of the proposed methodology is illustrated by means of its application to a particular financial data example. The dependence of the observations is a crucial factor in this work and is taken into account throughout the study.
Representing and aggregating conflicting beliefs
Authors: Pedrito Maynard-Zhang, Daniel Lehmann
Venue: Journal of Artificial Intelligence Research (2003)

We consider the two-fold problem of representing collective beliefs and aggregating these beliefs. We propose a novel representation for collective beliefs that uses modular, transitive relations over possible worlds. They allow us to represent conflicting opinions and they have a clear semantics, thus improving upon the quasi-transitive relations often used in social choice. We then describe a way to construct the belief state of an agent informed by a set of sources of varying degrees of reliability. This construction circumvents Arrow's Impossibility Theorem in a satisfactory manner by accounting for the explicitly encoded conflicts. We give a simple set-theory-based operator for combining the information of multiple agents. We show that this operator satisfies the desirable invariants of idempotence, commutativity, and associativity, and, thus, is well-behaved when iterated, and we describe a computationally effective way of computing the resulting belief state. Finally, we extend our framework to incorporate voting.
Sensor ranking: A primitive for efficient content-based sensor search
Authors: B. Maryam Elahi, Kay Romer, Benedikt Ostermaier, Michael Fahrmair, Wolfgang Kellerer
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

The increasing penetration of the real world with embedded and globally networked sensors enables the formation of a Web of Things (WoT), where high-level state information derived from sensors is embedded into Web representations of real-world entities (e.g. places, objects). A key service for the WoT is searching for entities which exhibit a certain dynamic state at the time of the query, which is a challenging problem due to the dynamic nature of the sought state information and due to the potentially huge scale of the WoT. In this paper we introduce a primitive called sensor ranking to enable efficient search for sensors that have a certain output state at the time of the query. The key idea is to efficiently compute for each sensor an estimate of the probability that it matches the query and process sensors in the order of decreasing probability, such that effort is first spent on sensors that are very likely to actually match the query. Using real data sets, we show that sensor ranking can significantly improve the efficiency of content-based sensor search.
Terminology Extraction from Log Files
Authors: Hassan Saneifar, Stéphane Bonniol, Anne Laurent, Pascal Poncelet, Mathieu Roche
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

The log files generated by digital systems can be used in management information systems as the source of important information on the condition of systems. However, log files are not exhaustively exploited in order to extract information. The classical methods of information extraction such as terminology extraction methods are irrelevant to this context because of the specific characteristics of log files like their heterogeneous structure, the special vocabulary and the fact that they do not respect a natural language grammar. In this paper, we introduce our approach Exterlog to extract the terminology from log files. We detail how it deals with the particularity of such textual data.
Inter-User Interference in Body Sensor Networks: Preliminary Investigation and an Infrastructure-Based Solution
Authors: Buddhika de Silva, Anirudh Natarajan, Mehul Motani
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

Inter-user interference is the interference in communication when several Body Sensor Networks (BSNs) operate in the same vicinity. As BSN users congregate in an area, interference due to concurrently communicating BSNs will increase, resulting in poor performance. In this paper, we conduct a preliminary investigation of the impact of inter-user interference and investigate its behavior with respect to parameters such as number of networks and the rates at which these networks communicate. Inter-user interference, is seen to reduce Packet Delivery Ratio by almost 35% in cases of 8 or more high-rate networks operating in the same location. We also propose a system to mitigate the adverse effects of inter-user interference. Our solution uses a fixed network infrastructure to monitor and identify BSNs that are likely to interfere with each other. The network then recommends changes to the BSN protocol to lessen interference between them. We also implement an instance of our system using a Wireless Sensor Network (WSN) infrastructure to reduce interference. The system is shown to significantly decrease the impact of inter-user interference.
Industrial E-Commerce and Visualization of Products: 3D Rotation versus 2D Metamorphosis
Authors: Francisco V. Cipolla Ficarra, Miguel Cipolla Ficarra, Daniel A. Giulianelli
Venue: Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009 (2009)

In this current work we make a study of communicability in industrial websites designed for the on-line sale of products, bearing in mind two kinds of 3D rotational animations, and 2D transformations. A table will be presented for the assessment of the communicability of the objects within e-commerce, in particular those which use mobile phones and the Internet. Also presented will be guidelines for qualitative design that may be employed without the need for a usability lab. The universe of study consists of 20 websites, randomly chosen from a total of 200. The contents of these websites is related to electronics, mechanics and renewable energy.
Efficient solution algorithms for factored MDPs
Authors: Carlos Guestrin, Daphne Koller, Ronald Parr, Shobha Venkataraman
Venue: Journal of Artificial Intelligence Research (2003)

This paper addresses the problem of planning under uncertainty in large Markov Decision Processes (MDPs). Factored MDPs represent a complex state space using state variables and the transition model using a dynamic Bayesian network. This representation often allows an exponential reduction in the representation size of structured MDPs, but the complexity of exact solution algorithms for such MDPs can grow exponentially in the representation size. In this paper, we present two approximate solution algorithms that exploit structure in factored MDPs. Both use an approximate value function represented as a linear combination of basis functions, where each basis function involves only a small subset of the domain variables. A key contribution of this paper is that it shows how the basic operations of both algorithms can be performed efficiently in closed form, by exploiting both additive and context-specific structure in a factored MDP. A central element of our algorithms is a novel linear program decomposition technique, analogous to variable elimination in Bayesian networks, which reduces an exponentially large LP to a provably equivalent, polynomial-sized one. One algorithm uses approximate linear programming, and the second approximate dynamic programming. Our dynamic programming algorithm is novel in that it uses an approximation based on max-norm, a technique that more directly minimizes the terms that appear in error bounds for approximate MDP algorithms. We provide experimental results on problems with over 1040 states, demonstrating a promising indication of the scalability of our approach, and compare our algorithm to an existing state-of-the-art approach, showing, in some problems, exponential gains in computation time.
Are Ten Participants Enough for Evaluating Information Scent of Web Page Hyperlinks?
Authors: Christos Katsanos, Nikolaos Tselios, Nikolaos Avouris
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

Information scent of hyperlinks, that is the user's assessment of semantic relevance of navigation options in a webpage, has been identified as a critical factor in Web navigation. An important question in this context is to identify the minimum number of participants required to measure reliably information scent. A two phase study was conducted in an attempt to provide an answer to this question. In the first phase, involving 101 participants, ratings produced by different size subsets of participants were compared to those of the whole set. In the second phase, the ratings of these different size subsets of participants where compared with measures of behavior of 54 participants, who performed the same information navigation tasks using a typical web browser. Results indicate that representative estimates of information scent can be obtained from 10 participants in both cases. This finding has important implications for future scent-related studies.
An Interactive Robot Butler
Authors: Yeow Kee Tan, Dilip Limbu Kumar, Ridong Jiang, Liyuan Li, Kah Eng Hoe, Xinguo Yu, Li Dong, Chern Yuen Wong, Haizhou Li
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques (2009)

This paper describes a novel robotic butler, developed by a multi-disciplinary team of researchers. The robotic butler is capable of detecting and tracking human, recognize hand gestures, serving beverages and performs dialog conversation with guest about their interests and their preferences; and providing specific information on the facilities at Fusionopolis building and various technologies used by the robot. The robot employs an event driven dialogue management system (DMS) architecture, speech recognition, ultra wideband, vision understanding and radio frequency identification. All these components and agents that are integrated in the DMS architecture are modular and can be re-used by other applications. In this paper, we will first describe the design concept and the architecture of the robotic butler. Secondly, we will describe in detail the workings of the speech and vision technology as this paper mainly focuses on human-robot interaction aspects of the social robot. Lastly, this paper will highlight some key challenges that were faced during the implementation of speech and vision technology into the robot.
Ordinal Computability
Authors: Peter Koepke
Venue: Proceedings of the 5th Conference on Computability in Europe: Mathematical Theory and Computational Practice (2009)

Ordinal computability uses ordinals instead of natural numbers in abstract machines like register or Turing machines. We give an overview of the computational strengths of ¿-β-machines, where ¿ and β bound the time axis and the space axis of some machine model. The spectrum ranges from classical Turing computability to ¿-¿-computability which corresponds to Gödel's model of constructible sets. To illustrate some typical techniques we prove a new result on Infinite Time Register Machines (= ¿-¿-register machines) which were introduced in [6]: a real number x ¿ ¿ 2 is computable by an Infinite Time Register Machine iff it is Turing computable from some finitely iterated hyperjump 0(n).
Design and Evaluation of the Customized Product Color Combination Interface Based on Scenario Experience
Authors: Ying-Jye Lee, Cheih-Ying Chen, Fong-Gong Wu
Venue: Proceedings of the Symposium on Human Interface 2009 on ConferenceUniversal Access in Human-Computer Interaction. Part I: Held as Part of HCI International 2009 (2009)

The customized product color interface based on scenario experience is defined as the experienced marketing model in this study. There are 48 color combinations of the spatial image resulted from four scenario styles and 12 popular sofa colors. The image compositing technique is adopted to appear the 48 color combinations of the spatial image on computer screen. This study compares the difference between the experienced marketing model and traditional marketing model by using the evaluation items of Personal Involvement Inventory. Results show that eight evaluation items including interesting, exciting, means a lot to me, appealing, fascinating, valuable, involving, and needed for the experienced marketing model are significant better than the traditional marketing model. Besides, two evaluation items including important and relevant doesn't appear significance between the two models. Therefore, the entrepreneur who wants to display the color primarily commodity should design the customized color combination interface with scenario experience for consumers to take opportunity to find the appropriate products to meet with consumers' needs, so as to shorten communication time between entrepreneurs and consumers.
Bottom-Up Shape Analysis
Authors: Bhargav S. Gulavani, Supratik Chakraborty, Ganesan Ramalingam, Aditya V. Nori
Venue: Proceedings of the 16th International Symposium on Static Analysis (2009)

In this paper we present a new shape analysis algorithm. The key distinguishing aspect of our algorithm is that it is completely compositional, bottom-up and non-iterative. We present our algorithm as an inference system for computing Hoare triples summarizing heap manipulating programs. Our inference rules are compositional: Hoare triples for a compound statement are computed from the Hoare triples of its component statements. These inference rules are used as the basis for a bottom-up shape analysis of programs.Specifically, we present a logic of iterated separation formula (LISF) which uses the iterated separating conjunct of Reynolds [17] to represent program states. A key ingredient of our inference rules is a strong bi-abduction operation between two logical formulas. We describe sound strong bi-abduction and satisfiability decision procedures for LISF.We have built a prototype tool that implements these inference rules and have evaluated it on standard shape analysis benchmark programs. Preliminary results show that our tool can generate expressive summaries, which are complete functional specifications in many cases.
Design of Control System for Wind Turbine Electric Pitch
Authors: Yongwei Li, Shuxia Liu, Jiazhong Wang, Hongbo Zhang, Zhiping Lu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

The operating principle of an electric pitch system of wind turbine is introduced in this paper, and three-phase PMSM (permanent magnetism synchronous motor) is chosen as the executive motor of the proposed system. TMS320F2812 is designed as the core of the electric propeller servo control system hardware based on the analysis of the servo variable pitch control system's principle, and a system software programming is carried out. Simulation and experiment studies are performed using MATLAB. Simulation studies indicated that the new system generate superior results over conventional system such as the dynamic response of the servo system speed is fast, and efficiency can be effective in the proposed system.
Learning information status of discourse entities
Authors: Malvina Nissim
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

In this paper we address the issue of automatically assigning information status to discourse entities. Using an annotated corpus of conversational English and exploiting morpho-syntactic and lexical features, we train a decision tree to classify entities introduced by noun phrases as old, mediated, or new. We compare its performance with hand-crafted rules that are mainly based on morpho-syntactic features and closely relate to the guidelines that had been used for the manual annotation. The decision tree model achieves an overall accuracy of 79.5%, significantly outperforming the hand-crafted algorithm (64.4%). We also experiment with binary classifications by collapsing in turn two of the three target classes into one and retraining the model. The highest accuracy achieved on binary classification is 93.1%.
Fuzzy Control for Regulating Level of Pressure Support Ventilation
Authors: Weiwei Yi, Qi Zhang, Yueke Wang, Jiulong Xiong, Haiyan Qin
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

This paper proposes a fuzzy control for regulating level of pressure support ventilation (PSV). The control uses the expert knowledge of the qualitative relationship of the physiological parameters and the patient’s state. The physiological parameters include heart rate (HR), tidal volume (VT), respiratory rate (RR), arterial partial pressure of carbon dioxide (PaCO2) and arterial oxygen saturation (SaO2). A physical state controller, a tendency controller and a decision controller are designed to regulate the pressure support (PS) level on-line according to changing the adjustment experience of clinicians for the parameters of the ventilator into expert knowledge database by using fuzzy sets, and expressing physiological parameter values by using membership functions. Comparative results ofthesimulation and clinical cure show that the on-line regulation reduces the doctors’ work and ensures that the PS level adapts to patients’ physiological requirement accurately and fast, so as to make the process of weaning from ventilator smooth and comfortable.
Resonance Characteristic Analysis for Spur Gear Servo Mechanism
Authors: Zirong Luo, Dapeng Fan, Jianzhong Shang, Shaoshuai Miao, Zheng Yang, Xiaoming Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Spur gear servomechanism is widely used in photoelectric stabilization platform and other weapon system, its resonance characteristic directly determines the bandwidth, gain and stability of the whole subsystem. Taking Spur gear servo mechanisms as research aim, three degrees of freedom vibration differential equation of gear mesh is theorized, and the resonance equation of the servo mechanism is obtained through Laplace transform, and then the vibration characteristic of stabilization platform is analyzed by numerical analysis. A new kind of resonance frequency analysis method is proposed based on virtual test technology. The digital simulation model of mechanism is created in MATLAB, and then the virtually frequency sweep method is used to excite the resonance characteristic of servo mechanism. The resonance frequency was obtained by analysis of curve of servo mechanism in time domain and frequency domain. Result of numerical analysis and virtual test show that the inertia moment of high speed axes and the mesh stiffness of gear are key assembly and sensitive parameter of the Spur gear servomechanism.