ppxscal/embedding_network huggingface dataset:
Modeling and Prediction of Heavy Metal Pollution in Mining Areas Based on Grey Model GM (1, 1)
Authors: Shuitai Xu, Lingyan Xiong, Yunzhang Rao, Jianping Pan
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Heavy metal pollution in mining areas possesses the character of grey system, so grey model GM (1, 1) can be used to predict heavy metal pollution. On the basis of heavy metal monitoring data in a certain sulfide mining area from 2006 to 2008, prediction models of copper (Cu), manganese (Mn) and lead (Pb) in mining areas have been built with grey model GM (1, 1) to predict heavy metal pollution contents in the mining area from 2009 to 2011, the accuracy of which meets the requirements after testing, and the projected results are credible. The prediction results show that in the next few years heavy metal Cu and Pb contents in the mining area will gradually increase, and Mn content decrease, but the mine is still in the state of pollution.
The Poisson Cluster Process Runs as a Model for the Internet Traffic
Authors: Jerzy Martyna
Venue: Proceedings of the 9th International Conference on Smart Spaces and Next Generation Wired/Wireless Networking and Second Conference on Smart Spaces (2009)

In this paper, we investigated a Poisson cluster process as runs of packet arrivals on the Internet. This model assumes that the Poisson cluster process is characterized by runs of packets which correspond to defined clusters in the Poisson process. Using the form of the length runs we studied the probability of a general number of cluster runs in the data stream. We illustrated how the obtained results can be used for the analysis of the real-life Internet traffic. 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
Decision-Tree-Based Automatic Filtering and Recovery of Signal Tracking in GPS Software Receiver
Authors: Shaodong Hou, Kedong Wang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

This paper presents a decision-tree-based automatic (DTBA) signal filtering and recovery algorithm in the tracking procedure of GPS software receiver. In the first part, the basic digital tracking loop is proposed. The loop consists of phase lock loop (PLL), frequency lock loop (FLL) and delay lock loop (DLL). In the second part, an automatic decision-tree-based algorithm is proposed to handle some exceptional cases when the traditional tracking loop is difficult to work, and retrieve the original signals as much as possible. When the original signals are totally disordered, the DTBA detects and outputs zero signals to avoid producing error navigation bit (D code). The simulations show that over 95% of invalid signals are retrieved with the algorithm. And the shape of the signal wave became clear after correction.
`I Have Something to Say': Supporting Aphasics for Organizing and Sharing Personal Experiences by Photos
Authors: Abdullah Al Mahmud, Jean-Bernard Martens
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

When a person, due to brain injury or other 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. We report on our early design exploration to share everyday experiences by photos for people having expressive aphasia. We also introduce the concept of a multimodal narrative template to help persons with aphasia to reconstruct their experiences and hence promote face-to-face communication and social interaction from everyday activities.
Reactive combination of belief over time using direct perception
Authors: Robin R. Murphy, Dale K. Hawkins, Marcel J. Schoppers
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

One issue for autonomous mobile robots operating in unknown, or partially known, domains is how to handle uncertainty in their sensor observations over time. Methods such as probablistic belief networks and survivor functions are generally unsatisfactory because they require explicit models of the robot's interactions with its environment, including possible contravening events. This information is difficult to obtain, and is philosophically incompatible with reactive behaviors. This paper presents an approach which eliminates the need for explicit models and reasoning; instead, it relies solely on directly perceivable attributes of the robot, object, and environment. The attributes qualitatively rate whether the robot's current observations are from an inherently more informed state than previous readings (e.g., from a better viewpoint). Observations from more informed states have different rates for the accrual and attrition of belief than those taken from less informed states. This paper describes the implementation, focusing on how the information state is computed using fuzzy logic, and how the state dynamically adapts a variation of Dempster's rule to generate the total belief. Data from a mobile robot tracking an unknown object demonstrates that the reactive computation of belief over time performs well for six canonical accrual and attrition cases.
User-Definable Rule Description Framework for Autonomous Actor Agents
Authors: Narichika Hamaguichi, Hiroyuki Kaneko, Mamoru Doke, Seiki Inoue
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

In the area of text-to-video research, our work focuses on creating video content from textual descriptions, or more specifically, the creation of TV program like content from script like descriptions. This paper discusses a description framework that can be used to specify rough action instructions in the form of a script that can be used to produce detailed instructions controlling the behavior and actions of autonomous video actor agents. The paper also describes a prototype text-to-video system and presents examples of instructions for controlling an autonomous actor agent with our designed descriptive scheme.
On the Termination Problem for Declarative XML Message Processing
Authors: Tadeusz Litak, Sven Helmer
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

We define a formal syntax and semantics for the Rule Definition Language (RDL) of DemaqLite, which is a fragment of the declarative XML message processing system Demaq. Based on this definition, we prove that the termination problem for any practically useful sublanguage of DemaqLiteRDL is undecidable, as any such language can emulate a Single Register Machine--a Turing-complete model of computation proposed by Shepherdson and Sturgis.
HomeNL: Homecare Assistance in Natural Language. An Intelligent Conversational Agent for Hypertensive Patients Management
Authors: Lina Maria Rojas-Barahona, Silvana Quaglini, Mario Stefanelli
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

The prospective home-care management will probably offer intelligent conversational assistants for supporting patients at home through natural language interfaces. Homecare assistance in natural language, HomeNL, is a proof-of-concept dialogue system for the management of patients with hypertension. It follows up a conversation with a patient in which the patient is able to take the initiative. HomeNL processes natural language, makes an internal representation of the patients' contributions, interprets sentences by reasoning about their meaning on the basis of a medical-knowledge representation and responds appropriately. HomeNL's aim is to provide a laboratory for studying natural language processing (NLP) and intelligent dialogues in clinical domains.
Moderating effects of task characteristics on information source use: An individual-level analysis of R&D professionals in new product development
Authors: Guo Bin
Venue: Journal of Information Science (2009)

Through an individual-level analysis of R&D professionals in technology-based firms, the current study examines the moderating effects of task characteristics on the relationships between source characteristics and information source use in terms of use frequency and source internality, in the context of new product development. The results show that task characteristics moderate the effects of source characteristics on information source use. Specifically, task uncertainty moderates the effect of source accessibility on use frequency for both internal and external sources. The positive relationship between source accessibility and use frequency of information sources is stronger when task uncertainty is low than when it is high. Furthermore, the results reveal that task characteristics moderate the effects of source characteristics on source internality. The present study provides strong evidence that the key to understanding how task characteristics affect information source use and reconciling the disagreements between the least effort principle and the quality-driven perspective is to examine the moderating effects of task characteristics on information seeking behaviour, and take into account the potential substitution effect between internal and external sources in information seeking.
Standardization of SVG in Implementing WebGIS
Authors: Xuemin Dong, Yan Li
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

This paper proposed a framework using a spatial-extended standardized SVG to implement a WebGIS project on the client side. It proceeds with creating the SVG-based representation model to make SVG support a complete representation of spatial information first, and then a spatial-extended standardized SVG is proposed for a spatial publishing framework on the client side. It is also important to mention some storage strategies such as SVG database and GML application schema and its management needed to improve the efficiency of the system. Finally, the workflow of the approach is showed. The experimental results shown, it is a feasible and practical SVG WebGIS in the implementation.
GIS-Based Multi-criteria Evaluation of Land Use Suitability for Disaster Prevention in Tangshan City
Authors: Chen Yanhua, Zhu Qingjie, Lu Shilin
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

GIS-based Multi-Criteria Evaluation (MCE) method is the foundation of decision-making analysis for land use suitability evaluation, and Weighted Linear Combination (WLC) is a basic method of multi-criteria evaluation. The most important of WLC method is the calculation of factor weights. The application of Analytical Hierarchy Program (AHP) is analyzed to construct comparison matrix, relative weight matrix and consistency ratio. According to the data of disaster factors in Tangshan City, evaluation criteria based on distance are constructed, and cretia images of disaster factors are standardized. Comparison matrix, relative weight matrix and consistency ratio are calculated, and suitability of land use for disaster prevention in Tangshan City is worked out. Finally, the results are analyzed, and some advice is proposed for land use planning of disaster prevention.
Anti-counterfeiting Using Memory Spots
Authors: Helen Balinsky, Edward Mcdonnell, Liqun Chen, Keith Harrison
Venue: Proceedings of the 3rd IFIP WG 11.2 International Workshop on Information Security Theory and Practice. Smart Devices, Pervasive Systems, and Ubiquitous Networks (2009)

We propose a new hardware and software solution for anti-counterfeiting that puts product authentication directly into the hands of end-users, enabling them to be confident of the authenticity of a product regardless of the integrity of the distribution chain. This is made possible by a new type of tamper-resistant hardware chip, called "memory spot", which has a unique combination of small size, very fast on-air data rate, relatively large memory, and integrated security features, in conjunction with a novel authentication protocol. In addition, the low cost of these new chips makes our proposed solution even more compelling than possible alternatives. Example applications include pharmaceutical anti-counterfeiting, asset tracking, secure-ID, brand protection and warranty fraud prevention. We will take pharmaceutical anti-counterfeiting as an example to explain our solution. A prototype system has been built to demonstrate the feasibility of the proposed system.
A new data hiding scheme for binary image authentication with small image distortion
Authors: Younho Lee, Heeyoul Kim, Yongsu Park
Venue: Information Sciences: an International Journal (2009)

A new data hiding scheme for binary image authentication that has a small distortion of the cover image is proposed in this paper. Using the data-embedding algorithm that is based on Hamming codes, the proposed scheme embeds authentication information into the cover image with flipping only a small number of pixels. A special type of the pixels are selected and flipped by a new algorithm to minimize visual distortion. This new algorithm is based on ELSSM (Edge Line Segment Similarity Measure). Randomly shuffling the bit-order of the authentication information to be embedded, the information can only be extracted by the designated receiver who has the symmetric key. We employ two measurement metrics: miss detection rates for the degree of security and PSNR (Peak Signal-to-Noise Ratio) and ELSSM for the degree of the image distortion to demonstrate the feasibility of the proposed scheme. Using these metrics, we analyze the proposed scheme and the previous schemes. The analysis reveals that the proposed scheme requires less image distortion than the previous schemes whilst achieving the same level of the miss detection rate. Experimental results demonstrate that the proposed scheme is more resilient against recent steganalysis attacks than the previous schemes.
Application of Artificial Neural Network to Modeling of Pipeline Damage Prediction
Authors: Lu Shilin, Liu Tingquan, Chen Yanhua
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Because the damage of pipeline is controlled by many factors, such as fault movement, pipe-soil interaction, buried depth, etc., the relationship between pipeline damage and influencing factors is complicated. In order to predict the pipeline damage, predictive model is constructed on the basis of artificial neural network (ANN), in which the damage of pipeline becomes a nonlinear function of influence factors. According to eight groups sample data, MATLAB is applied to analyze the design of predictive model; influences of model structure, concealed layer number, neuron number of concealed layer, and training function, on the predictive results are analyzed. Model parameters and preferences are optimized, and predictive model of pipeline damage is determined based on results of numerical simulation. Finally, optimum model structure is worked out and some advice for modeling and protection of pipeline is proposed.
Granular Computing and Knowledge Reduction in Formal Contexts
Authors: Wei-Zhi Wu, Yee Leung, Ju-Sheng Mi
Venue: IEEE Transactions on Knowledge and Data Engineering (2009)

Granular computing and knowledge reduction are two basic issues in knowledge representation and data mining. Granular structure of concept lattices with application in knowledge reduction in formal concept analysis is examined in this paper. Information granules and their properties in a formal context are first discussed. Concepts of a granular consistent set and a granular reduct in the formal context are then introduced. Discernibility matrices and Boolean functions are, respectively, employed to determine granular consistent sets and calculate granular reducts in formal contexts. Methods of knowledge reduction in a consistent formal decision context are also explored. Finally, knowledge hidden in such a context is unraveled in the form of compact implication rules.
Optimizing Pointer Analysis Using Bisimilarity
Authors: Luke Simon
Venue: Proceedings of the 16th International Symposium on Static Analysis (2009)

We introduce a new technique for dramatically improving the performance of inclusion-based points-to analysis, by using bisimilarity in order to detect pointer equivalences before constraint resolution. We present the design and correctness proof of this technique, along with an implementation prototype, and a series of benchmarks. The benchmarks indicate that our technique dramatically improves the scalability of inclusion-based points-to analysis, beating the current leading offline optimizations for inclusion-based points-to analysis. 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
Generation of simple Turkish sentences with systemic-functional grammar
Authors: Ilyas Cicekli, Turgay Korkmaz
Venue: Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning (1998)

This paper mainly presents a Turkish sentence generator for producing the actual text from its semantic description. To concentrate on the text generation rather than text planning, we assume that the lexicalized semantic description of the text is produced in some way, currently given by hand. In the generation, we need a linguistic theory to describe the linguistic resources, and also a software tool to perform them in a computational environment. We use a functional linguistic theory called Systemic-Functional Grammar (SFG) to represent the linguistic resources, and FUF text generation system as a software tool to perform them. In this paper, we present the systemic-functional representation and realization of simple Turkish sentences.
Research and Practice of Web Server Optimization
Authors: Mingfu Wang, Zhiwen Qi
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

The application and development of Web technology is limited by the integrative performance of web server. Analyzed the principle of web service and the system’s overloading, showed the critical parts that influence mostly the performance of web server. An optimize solution based on Java scheme was given. An adaptive loading balance scheme was presented using distribute buffer pool technique. The benefit was evaluated and analyzed. It is proved in both theory and practice that the solution is adaptive and valuable.
Classification Techniques for Talent Forecasting in Human Resource Management
Authors: Hamidah Jantan, Abdul Razak Hamdan, Zulaiha Ali Othman
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

Managing an organization's talents, especially in assigning the right person to the right job at the right time is among the top challenge for Human Resource (HR) professionals. This article presents an overview of talent management problems that can be solved by using classification and prediction method in Data mining. In this study, talent's performance can be predicted by using past experience knowledge in HR databases. For experiment purposes, we used the possible classification and prediction techniques in order to find out the suitable techniques for HR data. An example demonstrates the feasibility of the suggested classification techniques using selected employee's performance data. Finally, the initial experiment results show the potential classification techniques for talent forecasting in Human Resource Management (HRM).
A Chest Wall Model Based on Rib Kinematics
Authors: Anne-Laure Didier, Pierre-Frédéric Villard, Jacques Saade, Jean-Michel Moreau, Michaël Beuve, Behzad Shariat
Venue: Proceedings of the 2009 Second International Conference in Visualisation (2009)

The success of radiotherapy treatment could be compromised by motion. Lung tumours are particularly concerned by this problem because their positions are subject to breathing motion. To reduce the uncertainty on the position of pulmonary tumours during breathing cycle, we propose to develop a complete thoracic biomechanical model. This model will be monitored through the measurement of external parameters (thorax outer-surface motion, air flow...) and should predict in real-time the location of lung tumour. In this paper, we expose a biomechanical model of the lung environment, based on anatomical and physiological knowledge. The model includes the skin, the ribs, the pleura and the soft tissue between the skin and the ribcage. Motions and deformations are computed with the Finite Element Method. The ribcage direct kinematics model, permits to compute the skin position from the ribs motion. Conversely, the inverse kinematics provides rib motion and consequently lung motion. It can be computed from the outer-surface motion.With regards to available clinical data the results are promising. In particular, the average error is lower than the resolution of the CT-scan images used as input data.
Research on the Configuration of Reconfigurable Machine Tool Using Rough Set
Authors: Nan Xie, Aiping Li, Jianxin You, Siying Chen
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

To meet new needs of shorter production life cycleand changing product varieties, ReconfigurableManufacturing System (RMS) requires rapid reconfigurationfor related modules of Reconfigurable Machine Tool (RMT)according to different part features. Design and configurationof machine tool are closely linked with process plan features ofparts, so the selection of its configuration is to a great extentdependent on experience of technicians. In the paper, bothconfiguration selection scheme of RMT based part processfeatures and the acquisition method of configuration designknowledge are presented. Based on Artificial principle andmethod, the design and reconfiguration architecture for RMTis constructed and based on the architecture the configurationselection system for RMT is also developed which is based onRough Sets(RS) theory, extracts expert knowledge of designand configuration, and eventually presents needed results. Inthe last, a case is also presented to verify its effectivity andefficiency.
A variational learning algorithm for the abstract hidden Markov model
Authors: Jeff Johns, Sridhar Mahadevan
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

We present a fast algorithm for learning the parameters of the abstract hidden Markov model, a type of hierarchical activity recognition model. Learning using exact inference scales poorly as the number of levels in the hierarchy increases; therefore, an approximation is required for large models. We demonstrate that variational inference is well suited to solve this problem. Not only does this technique scale. but it also offers a natural way to leverage the context specific independence properties inherent in the model via the fixed point equations. Experiments confirm that the variational approximation significantly reduces the time necessary for learning while estimating parameter values that can be used to make reliable predictions.