ppxscal/embedding_network huggingface dataset:
A Method for Developing Plug-and-Play Web GIS
Authors: Zhou Di-bo, Pan De-lu
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

Web GIS is one of the hot topics today. Because of its professional characteristic, a Web GIS application often requires complicated configuration before it can be used. In this paper, a method to develop pre-configured plug-and-play Web GIS is presented for saving the energy and time needed by the installation, configuration, and maintenance of Web GIS. According to the method, two systems, original system and memory running system are set up on a USB flash drive. A Web GIS integrated environment is founded on the USB flash drive as original system and the memory running system runs as a mirror of the USB flash drive original system. The memory running system is deployed into RAM from USB flash drive during system boot process using tmpfs and initrd. Operating system, applications and geo-spatial data are totally in RAM to offer good performance, and the erase cycles limitation of USB flash drive is overcome by this way. System updates are realized through the USB flash drive original system and then applied to the memory running system. To verify the validity of this method, a plug-and-play Web GIS prototype was developed based on Debian GNU/Linux. The prototype combines Linux, Web GIS, tmpfs (a ramdisk mechanism in Linux) and initrd technique into a Web GIS integrated environment that can be used to publish geo-spatial data efficiently on different computers through USB interface. The actual operation on different PC servers indicates the prototype is very efficient. With steady improvements in price, capacity, speed of USB flash drive and RAM, this method is expected to be widely applied.
Application-Driven Analytic Toolbox for WSNs
Authors: Jussi Haapola, Flavia Martelli, Carlos Pomalaza-Ráez
Venue: Proceedings of the 8th International Conference on Ad-Hoc, Mobile and Wireless Networks (2009)

In this paper we propose a Generic Analytical DesiGn EnvironmenT (GADGET) Toolbox for designing the most suitable MAC protocol for an arbitrary wireless sensor network (WSN) application. Furthermore, a model to weight the metrics in the design and a new single compound metric are proposed. Comparing performance curves produced by a number of metrics make it difficult to evaluate how well a given protocol suits for the purposes of an application. It may also be difficult to estimate, which of the protocols at hand would perform the best with respect to that application. Matching the application with the most appropriate protocols is critical for efficient WSN operation because the sensor nodes are resource constrained by nature. The analytic hierarchy process and a pair-wise weighted comparison of the protocols enable to emphasise application performance requirements and to produce a single performance curve either by combination of competing protocols (fractional) or per protocol (absolute). The former provides suitability of one protocol over others with respect to an application whereas the latter provides also insight on the absolute performance of the protocol.
CMOS 2.45GHz RF power amplifier for RFID reader
Authors: M. J. Uddin, M. I. Ibrahimy, M. A. Hasan, M. A. M. Ali, M. B. I. Reaz
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

A high linearity CMOS RF (radio frequency) power amplifier, which has the advantage of being low-cost and easily integrated on chip has become the technology of choice for RFID readers. This work demonstrates a 3.3V single voltage self-biased 2.4GHz--2.5GHz high linearity RF power amplifier for RFID applications.
Mapping XML DTD to Relational Schema
Authors: Feng Ye, Xiao Jingsheng
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

This paper discusses the method to achieve mapping XML DTD to Relational Schema. It expresses the nodes, attributes and semantic constraints of XML DTD by using ADG. It then optimizes the ADG, and finally converts ADG to relational schema. This article gives the algorithm steps of creating ADG by DTD, the optimization of ADG and the transformation rule from semantic constraints of ADG to semantic constraints of Relational Schema. The method cannot only obtain the structure information of DTD, but also maintain the semantic constraint of DTD.
Component mode synthesis methods using partial interface modes: Application to tuned and mistuned structures with cyclic symmetry
Authors: Duc-Minh Tran
Venue: Computers and Structures (2009)

We present new component mode synthesis methods using partial interface modes which are the structure normal modes resulting from the static condensation of the structure to the interface between the substructures and which are possibly clamped at a part of this interface. These methods are the generalization of the classical component mode synthesis methods and those using the interface modes. These methods allow to reduce the number of the interface coordinates and at the same time to keep some of the physical interface displacements. These methods are applied to a structure with cyclic symmetry in both tuned and mistuned cases.
A characteristics-mixed covolume method for a convection-dominated transport problem
Authors: Haitao Che, Ziwen Jiang
Venue: Journal of Computational and Applied Mathematics (2009)

In this paper, we propose a characteristics-mixed covolume method for approximating the solution to a convection dominated transport problem. The method is a combination of characteristic approximation to handle the convection term in time and mixed covolume method spatial approximation to deal with the diffusion term. The velocity and press are approximated by the lowest order Raviart-Thomas mixed finite element space on rectangles. The projection of a mixed covolume element is introduced. We prove its first order optimal rate of convergence for the approximate velocities in the L^2 norm as well as for the approximate pressures in the L^2 norm.
System Model of Three-Level Switching Power Amplifier for Magnetic Bearing
Authors: Jun Wang, Longxiang Xu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Switching power amplifier for magnetic bearing is a nonlinear system. An accurate system model is presented. According to the operating modes of three-level switching power amplifier, the math model of power amplifier based on the state-space averaging model is deduced. By using this math model, the closed-loop system transfer function can be analyzed. The PI controller parameter can be designed according to the request of system dynamic response. The simulation and experiment of system are made and the results show that the proposed model provides the dynamic characteristics more closely resembling the actual power amplifier circuit behavior. The model has clear physical meaning and is feasible and effective.
Almost periodic solution to Cohen-Grossberg-type BAM networks with distributed delays
Authors: Hongjun Xiang, Jinhua Wang, Jinde Cao
Venue: Neurocomputing (2009)

In this paper, a class of Cohen-Grossberg-type bi-directional associative memory (BAM) neural networks with distributed delays is discussed. Based on inequality analysis method and combining the exponential dichotomy with fixed point theorem, some novel sufficient conditions are obtained to ensure the existence and globally exponential stability of almost periodic solution to this system. Moreover, an example is given to demonstrate the feasibility of our results.
Automatic slide presentation from semantically annotated documents
Authors: Utiyama Masao, Hasida Kôiti
Venue: Proceedings of the Workshop on Coreference and its Applications (1999)

This paper discusses how to automatically generate slide shows. The reported presentation system inputs documents annotated with the GDA tagset, an XML tagset which allows machines to automatically infer the semantic structure underlying the raw documents. The system picks up important topics in the input document on the basis of the semantic dependencies and coreferences identified from the tags. This topic selection depends also on interactions with the audience, leading to dynamic adaptation of the presentation. A slide is composed for each topic by extracting relevant sentences and paraphrasing them to an itemized summary. Some heuristics are employed here for paraphrasing and layout. Since the GDA tagset is independent of the domain and style of documents and applicable to diverse natural languages, the reported system is also domain/style independent and easy to adapt to different languages.
2D Partial Similarity Estimation Based on Energy Segmentation II. Feature based Similarity Calculation
Authors: Fan Yamin, Zhang Mabiao, Liu Yusheng
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

How to perform partial similarity between models is still an open issue and attracts many attentions. Segmentation is regarded as one of the most critical and prospective steps for overcoming the task. An energy based segmentation approach for 2D curve is proposed in this paper. A curve is regarded as an elastic stripline(like spring) which has the balanced state and unbalanced state. Once it lies on the unbalanced state such as a spring elongated or compressed, it will possess the potential energy. Then the segmentation can be performed smoothly based on the energy and its attribute. Important is that no thresholds are required to initially determine the segmentation compared with the other methods. Also the proposed algorithm has several important and interesting properties such as robustness, independence, invariance and efficiency
Automatic Target Detection and Analyses in Side-scan Sonar Imagery
Authors: Wen-Miin Tian
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

The purpose of the current investigation was dedicated to the development of an automatic side-scan sonar imagery analysis program for the detection and identification of stationary targets, such as meter-sized concrete artificial reefs, on the sea floor. The major components of the program include: image acquisition; feature extraction; feature classification; target identification; and target properties analyses. Program verification and optimal parameters determination were conducted with a high quality sonograph of 650 x 650 pixels. Optimal parameters, i.e., a region size of 38 x 38 pixels, a region sliding distance of 4 pixels and 16 quantized grey levels for this specific type of image were determined. A realistic evaluation of this program was conducted and proved successful. The automatic image analysis program based on grey level co-occurrence matrix, unsupervised Bayesian classifier and hierarchical cluster analysis can improve the detection and identification of stationary targets in side-scan sonar imagery. It offered a potential for the development of a completely automatic system for the detection of stationary target in real time at sea.
Graph-based keyword extraction for single-document summarization
Authors: Marina Litvak, Mark Last
Venue: Proceedings of the Workshop on Multi-source Multilingual Information Extraction and Summarization (2008)

In this paper, we introduce and compare between two novel approaches, supervised and unsupervised, for identifying the keywords to be used in extractive summarization of text documents. Both our approaches are based on the graph-based syntactic representation of text and web documents, which enhances the traditional vector-space model by taking into account some structural document features. In the supervised approach, we train classification algorithms on a summarized collection of documents with the purpose of inducing a keyword identification model. In the unsupervised approach, we run the HITS algorithm on document graphs under the assumption that the top-ranked nodes should represent the document keywords. Our experiments on a collection of benchmark summaries show that given a set of summarized training documents, the supervised classification provides the highest keyword identification accuracy, while the highest F-measure is reached with a simple degree-based ranking. In addition, it is sufficient to perform only the first iteration of HITS rather than running it to its convergence.
Multi-agent Cooperation: A Description Logic View
Authors: Jiewen Luo, Zhongzhi Shi, Maoguang Wang, He Huang
Venue: Multi-Agent Systems for Society: 8th Pacific Rim International Workshop on Multi-Agents, PRIMA 2005, Kuala Lumpur, Malaysia, September 26-28, 2005, Revised Selected Papers (2009)

In this paper we propose dynamic description logic for formalizing multi-agent cooperation process with a clearly defined syntax and semantics. By combining the features of knowledge representation and reasoning of description logic and action theory for multi-agent interaction, our logic is effective and significant both for static and dynamic environment. On the static side, we employ description logic for the representation and reasoning of beliefs and goals. On the dynamic side, we adopt the object-oriented method to describe actions. The description of each action is composed of models, preconditions and effects. It can reflect the real changes of the world and is very suitable for belief revision and action planning. Based on our logic, we investigate how to form joint goal for multi-agent cooperation. In particular, we propose an effective dynamic planning algorithm for scheduling sub goals, which is greatly crucial for coordinating multi-agent behaviors.
A Survey on Privacy Preserving Approaches in Data Publishing
Authors: Yan Zhao, Ming Du, Jiajin Le, Yongcheng Luo
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Privacy preserving in data publishing has become one of the most important research topics in data security field and it has become a serious concern in publication of personal data in recent years. How to efficiently protect individual privacy in data publishing is especially critical. Thus, various proposals have been designed for privacy preserving in data publishing. In this paper, we summarize privacy preserving approaches in data publishing and survey current existing techniques, and analyze the advantage and disadvantage of these approaches. We divide these proposals into two categories, one is to achieve the purpose of privacy preserving based on k-anonymity model, and the other is to utilize the methods of probability or statistics to protect data privacy in the case of the statistical properties of the final data and classification properties are unchanged. For example, clustering, randomization approaches. Finally, we discuss the future directions of privacy preserving in data publishing.
Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents
Authors: Nicoletta Noceti, Barbara Caputo, Claudio Castellini, Luca Baldassarre, Annalisa Barla, Lorenzo Rosasco, Francesca Odone, Giulio Sandini
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

Multi-modality is a fundamental feature that characterizes biological systems and lets them achieve high robustness in understanding skills while coping with uncertainty. Relatively recent studies showed that multi-modal learning is a potentially effective add-on to artificial systems, allowing the transfer of information from one modality to another. In this paper we propose a general architecture for jointly learning visual and motion patterns: by means of regression theory we model a mapping between the two sensorial modalities improving the performance of artificial perceptive systems. We present promising results on a case study of grasp classification in a controlled setting and discuss future developments.
Nonnegative Mixed-Norm Preconditioning for Microscopy Image Segmentation
Authors: Kang Li, Takeo Kanade
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

Image segmentation in microscopy, especially in interference-based optical microscopy modalities, is notoriously challenging due to inherent optical artifacts. We propose a general algebraic framework for preconditioning microscopy images. It transforms an image that is unsuitable for direct analysis into an image that can be effortlessly segmented using global thresholding. We formulate preconditioning as the minimization of nonnegative-constrained convex objective functions with smoothness and sparseness-promoting regularization. We propose efficient numerical algorithms for optimizing the objective functions. The algorithms were extensively validated on simulated differential interference (DIC) microscopy images and challenging real DIC images of cell populations. With preconditioning, we achieved unprecedented segmentation accuracy of 97.9% for CNS stem cells, and 93.4% for human red blood cells in challenging images.
Reactive and dynamic local search for max-clique: Engineering effective building blocks
Authors: Roberto Battiti, Franco Mascia
Venue: Computers and Operations Research (2010)

This paper presents the results of an ongoing investigation about how different algorithmic building blocks contribute to solving the maximum clique problem. We consider greedy constructions, plateau searches, and more complex schemes based on dynamic penalties and/or prohibitions, in particular the recently proposed technique of dynamic local search and the previously proposed reactive local search (RLS). We design a variation of the original RLS algorithm where the role of long-term memory (LTM) is increased (RLS-LTM). In addition, we consider in detail the effect of the low-level implementation choices on the CPU time per iteration. We present experimental results on randomly generated graphs with different statistical properties, showing the crucial effects of the implementation, the robustness of different techniques, and their empirical scalability.
COBRA --- A Visualization Solution to Monitor and Analyze Consumer Generated Medias
Authors: Amit Behal, Julia Grace, Linda Kato, Ying Chen, Shixia Liu, Weijia Cai, Weihong Qian
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)

Consumer Generated Medias (CGMs) --- such as blogs, news forums, message boards, and web pages --- are emerging as locations where consumers trade, discuss and influence each other's purchasing patterns. Leveraging such CGMs to provide valuable insight into consumer opinions and trends is becoming increasingly attractive to corporations. This paper describes COBRA (COrporate Brand and Reputation Analysis), a visual analytics solution that surfaces the text mining and statistical analysis capabilities described in our earlier COBRA papers. Our interaction technique of search, visualization, and monitor enables detailed analysis of many CGMs without overwhelming the user. A suite of visualization solutions expose a variety of embedded COBRA visual analytics capabilities. Real world client engagements and user studies demonstrate the effectiveness of our approach.
ICT Is Not Participation Is Not Democracy --- eParticipation Development Models Revisited
Authors: Åke Grönlund
Venue: Proceedings of the 1st International Conference on Electronic Participation (2009)

There exist several models to describe "progress" in eParticipation. Models are typically ladder type and share two assumptions; progress is equalled with more sophisticated use of technology, and direct democracy is seen as the most advanced democracy model. None of the assumptions are true, considering democratic theory, and neither is fruitful as the simplification disturbs analysis and hence obscures actual progress made. The models convey a false impression of progress, but neither the goal, nor the path or the stakeholders driving the development are clearly understood, presented or evidenced. This paper analyses commonly used models based on democratic theory and eParticipation practice, and concludes that all are biased and fail to distinguish between the three dimensions an eParticipation progress model must include; relevance to democracy by any definition, applicability to different processes, (capacity building as well as decision making), and measuring different levels of participation without direct democracy bias.
Statistical Machine Translation from Slovenian to English Using Reduced Morphology
Authors: Mirjam Sepesy Maučec, Janez Brest
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)

This paper describes the study of word-based statistical machine translation to language pair Slovenian - English. The problem when dealing with Slovenian language is data sparsity and consequently, error-full translations. The aim of the work is to define the approach to reduce the inflectional morphology of the Slovenian language for translation into less inflected language. The reduction is performed by a Differential Evolution algorithm, which belongs to Evolutionary Algorithms, and is widely used for global optimization problems. The experiments were carried out using a freely-available parallel English-Slovenian SVEZ-IJS corpus, which is lemmatised and annotated with morpho-syntactic description (MSD) tags. A set of baseline experiments is described and compared with experiments done on reduced MSD tags. The paper reports an improvement in translation results when compared to using words, lemmas and fully morpho-syntactically annotated words.
A Webgis Load-Balancing Algorithm Based on Collaborative Task Clustering
Authors: Huang Ying, Guo Mingqiang, Luo Xiangang, Liu Yong
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

This paper analyzes deficiencies of load-balancing technologies in the current webgis and discusses the necessity and feasibility to solve load-balancing in webgis through server farms. A new distributed dynamic scheduling model based on server farms is given. A webgis load-balancing algorithm based on collaborative task clustering is proposed. The new algorithm divides the collaborative computing task into n subtasks; then generates collaborative task clustering; at last, dynamically allocate them to every gis server which is in the above model. It maximizes the execution time of collaborative spatial computing; effectively improve the utilization and the parallel processing capacity of webgis; provides faster and better webgis service for users. A test-bed is established. A series of test results prove that the algorithm has good global load balancing performance.
A Superresolution Framework for High-Accuracy Multiview Reconstruction
Authors: Bastian Goldlücke, Daniel Cremers
Venue: Proceedings of the 31st DAGM Symposium on Pattern Recognition (2009)

We present a variational approach to jointly estimate a displacement map and a superresolution texture for a 3D model from multiple calibrated views. The superresolution image formation model leads to an energy functional defined in terms of an integral over the object surface. This functional can be minimized by alternately solving a deblurring PDE and a total variation minimization on the surface, leading to increasingly accurate estimates of photometry and geometry, respectively. The resulting equations can be discretized and solved on texture space with the help of a conformal atlas. The superresolution approach to texture reconstruction allows to obtain fine details in the texture map which surpass individual input image resolution.