ppxscal/embedding_network huggingface dataset:
CASQUS: A new simulation tool for coupled 3D finite element modeling of tectonic and surface processes based on ABAQUSTM and CASCADE
Authors: Daniel Kurfeí, Oliver Heidbach
Venue: Computers Geosciences (2009)

CASQUS is a numerical simulation tool to model the feedback mechanism between surface and tectonic processes. It includes the surface processes model CASCADE into the finite element solver ABAQUS/Standard(TM). The finite element method allows for geomechanical simulations of the subsurface with geometrically complex structures in 3D. Additionally, in the commercial software ABAQUS(TM) various types of rheological behavior are already implemented. CASCADE simulates erosion and sedimentation as the combination of fluvial transport and hillslope processes. For the integration of CASCADE into ABAQUS/Standard(TM) an Arbitrary Lagrangian-Eulerian modeling technique is used, which makes a coupled and automated simulation possible. Two benchmark models that are easy to reproduce demonstrate the functionality of CASQUS. Our tool aims at a better understanding of the feedback between mass redistribution at the Earth's surface and processes within a heterogenous subsurface, and at a quantification of the involved processes.
Impromptu teams of heterogeneous mobile robots
Authors: Ross Mead, Jerry B. Weinberg
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

As robots become more involved in assisting us in large and hazardous operations, such as search and rescue, we can anticipate that diverse robots will come together with the need to coordinate their efforts. These robots will come from different organizations, creating a heterogeneous team, varying in shape, size, and functionality. How can diverse robots forming such an impromptu team collaborate to accomplish a joint objective? If they are to organize and work together, methods must be developed that allow them to share knowledge in a meaningful way. We propose an ontology-based symbolic communication protocol to provide a shared understanding of physical concepts between units. Coordination is then accomplished through a negotiation of tasks to complete individual and joint goals.
Liberalization policy, production and cost efficiency in Taiwan's telecommunications industry
Authors: Chao-Chung Kang
Venue: Telematics and Informatics (2010)

Many economists, policy-makers, and corporate managers have long believed that the operational performance of private enterprises is much more efficient than that of public utilities. However, some researches on changes in efficiency before and after privatization contradict this. The purpose of this paper is to analyze changes in technical and cost efficiency in Chunghwa Telecom Company (CHT) before and after partial privatization. The input-orientation Data Envelopment Analysis (DEA) and Cost-DEA were the research tools used in this study, and the findings showed that the technical efficiency, allocation efficiency, and cost efficiency become worse after partial privatization. Additionally, we found that CHT cannot achieve any significant improvement in cost management under its partial privatization environment. CHT is still restricted by government policies and regulations, thus undermining its ability to achieve any significant improvement in its cost management. In order to improve efficiency for CHT, the government needs to eliminate some regulations and relax its control over CHT, thus creating a completely privatized environment.
Efficient keyword proximity search using a frontier-reduce strategy based on d-distance graph index
Authors: Ming Zhong, Mengchi Liu
Venue: Proceedings of the 2009 International Database Engineering & Applications Symposium (2009)

Current keyword proximity search approaches on general graph lack effective means to reduce the search space, and thus suffer from low efficiency when dealing with large search space. In this paper, we present a novel approach in order to address this problem. Our approach employs a best-effort frontier-reduce strategy that aims to find a set of subgraphs containing the best answers. So we need only to search over these small subgraphs to get the top-k answers, and thus the efficiency can be significantly improved. To fulfill our strategy, we define a d-distance subgraph with upper size bound, and extract such subgraphs from the graph to build a new index structure combining the mappings between keywords, vertexes and subgraphs, by which we can quickly look up the target subgraphs for specific queries. Then, we perform an efficient algorithm to find the top-k answers, which can overcome the subgraph overlap problem and support existing optimal prioritization techniques. Lastly, we evaluate the effectiveness and efficiency of our approach with extensive experiments. The experimental results show that our approach can outperform existing approaches by a large margin with little or none loss of answer quality.
ViroLab Security and Virtual Organization Infrastructure
Authors: Jan Meizner, Maciej Malawski, Eryk Ciepiela, Marek Kasztelnik, Daniel Harezlak, Piotr Nowakowski, Dariusz Król, Tomasz Gubała, Włodzimierz Funika, Marian Bubak, Tomasz Mikołajczyk, Paweł Płaszczak, Krzysztof Wilk, Matthias Assel
Venue: Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies (2009)

This paper introduces security requirements and solutions present in the ViroLab Virtual Laboratory. Our approach is to use a federated Single Sign-On mechanism based on the Shibboleth framework that enables multiple partners to authenticate against their local identity systems and use resources provided by all other partners. Since the basic Shibboleth capabilities do not meet our specific requirements related to supporting non-web-based services, we created a set of custom tools that allow us to develop a homogeneous, Shibboleth-based security solution for both Web and non-web-based software components. This paper describes these tools in detail, together with other services of the virtual laboratory which have been integrated with the security infrastructure. A decentralized, attribute-based approach facilitating the creation and management of virtual organizations is the key achievement of our work.
Enabling large-scale storage in sensor networks with the Coffee file system
Authors: Nicolas Tsiftes, Adam Dunkels, Zhitao He, Thiemo Voigt
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

Persistent storage offers multiple advantages for sensor networks, yet the available storage systems have been unwieldy because of their complexity and device-specific designs. We present the Coffee file system for flash-based sensor devices. Coffee provides a programming interface for building efficient and portable storage abstractions. Unlike previous flash file systems, Coffee uses a small and constant RAM footprint per file, making it scale elegantly with workloads consisting of large files or many files. In addition, the performance overhead of Coffee is low: the throughput is at least 92% of the achievable direct flash driver throughput. We show that network layer components such as routing tables and packet queues can be implemented on top of Coffee, leading to increased performance and reduced memory requirements for routing and transport protocols.
A Study of Retrieval Land Surface Temperature and Evapotranspiration in Response to LUCC Based on Remote Sensing Data in Sanggong River
Authors: Cao Xiaoming, Bao Anming, Li Lanhai
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

The condition of land use/cover change (LUCC) is an important influence factor of the land surface temperature (LST) and the evapotranspiration (ET). Herein LST and ET were retrieved by Qin et al’s mono-window algorithm and SEBAL model, respectively, based on landsat TM/ETM+ data. The analysis of retrieval result indicated that the change of the land use/cover was remarkable during 9 years from 1990 to 1999 in the Sangong River in Fukang of Xinjiang province. The land use/cover characteristics mainly controlled the spatial distribution of the LST and ET. The distributions of LST and ET were all a single-apex model over different land use/cover. The frequency distribution characteristic of LST in 1999 was roughly consistent with those in 1990, but the change ranges of LST over different land use/cover in 1999 were large than those in 1990. ET has presented the same change characteristic, and the day ETs of 1999 over different land use/cover were larger than those of 1990.The results demonstrate that LST possessed evidently negative correlation with the ET for all land cover types.
Teaching Experiences on Course of Comprehensive Practice of Program Design
Authors: Xu Min, Zhou Lijuan
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

In this paper, to use inquiry-based teaching model to improve teaching quality is discussed. Comprehensive Practice of Program Design is a practical course of computer science major. During the teaching practice on this course, author attempted to apply inquiry-based teaching model. It is concluded as four issues: task-driven teaching, thought-provoking instructions, self-studying strategy and cultivating teamwork skills. The most remarkable characteristic of inquiry-based teaching model is student-centered and teacher-guided. It changed the old cramming education which is a kind of passive learning model. What the inquiry-based teaching model advocate is lead-study, that is, students participate into the teaching process actively under the teacher's guide. This paper represents the summary of author's experiences about how to put these methods in teaching practice.
APOD: Anonymous Physical Object Delivery
Authors: Elli Androulaki, Steven Bellovin
Venue: Proceedings of the 9th International Symposium on Privacy Enhancing Technologies (2009)

Delivery of products bought online can violate consumers' privacy, although not in a straightforward way. In particular, delivery companies that have contracted with a website know the company selling the product, as well as the name and address of the online customer. To make matters worse, if the same delivery company has contracted with many websites, aggregated information per address may be used to profile customers' transaction activities. In this paper, we present a fair delivery service system with guaranteed customer anonymity and merchant-customer unlinkability, with reasonable assumptions about the threat model.
Adaptive particle swarm optimization for CNN associative memories design
Authors: Girolamo Fornarelli, Antonio Giaquinto
Venue: Neurocomputing (2009)

In this paper particle swarm optimization is used to implement a synthesis procedure for cellular neural networks autoassociative memories. The use of this optimization technique allows a global search for computing the model parameters that identify designed memories, providing a synthesis procedure that takes into account the robustness of the solution. In particular, the design parameters can be modified during the convergence in order to guarantee minimum recall performances of the network in terms of robustness to noise overlapped to input patterns. Numerical results confirm the good performances of the designed networks when patterns are affected by different kinds of noise.
Nonignorable dropout models for longitudinal binary data with random effects: An application of Monte Carlo approximation through the Gibbs output
Authors: Jennifer S. K. Chan, Doris Y. P. Leung, S. T. Boris Choy, Wai Y. Wan
Venue: Computational Statistics Data Analysis (2009)

The analysis of longitudinal data with nonignorable dropout remains an active area in biostatistics research. Nonignorable dropout (ND) refers to the type of dropout when the probability of dropout depends on the missing observations at or after the time of dropout. Failure to account for such dependence may result in biased inference. Motivated by a methadone clinic data of longitudinal binary observations with dropouts, we propose a conditional first order autoregressive (AR1) logit model for the outcome measurements. The model is further extended to incorporate random effects in order to account for the population heterogeneity and intra-cluster correlation. The purposed models account for the dropout mechanism by a separate logit model in some covariates and missing outcomes for the binary dropout indicators. For model implementation, we proposed a likelihood approach through Monte Carlo approximation to the Gibbs output that evaluates the complicated likelihood function for the random effect ND model without tear. Finally simulation studies are performed to evaluate the biases on the parameter estimates of the outcome model for different dropout mechanisms.
Constructing Customer's Value Analysis Model Based on Expert System for Leisure Farms
Authors: Feng Qian, Linwen Xu
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

CRM, which aims to enhance the effectiveness and performance of the businesses by mining the useful business intelligence of customers, has now become a leading business strategy in highly competitive business environment. In this study, we will intend to construct an expert system (ES) platform to address the customer’s value analysis based on artificial neural networks, and the construction procedure of value expansion and value prediction are effectively represented. Finally, an illustrative example owing to a leisure farm at Hangzhou in Zhejiang is also taken to demonstrate the feasibility and rationality of the proposed ES platform.
1/f Noise Reduction and Image Enhancement on CMOS Image Sensors by Autocorrelation Based on Adaptive Algorithm
Authors: Kunsu Hwang, T. H. Nishimura
Venue: Proceedings of the Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science 2008 (2008)

In CMOS image sensor, 1/f noise is determined by width and length of gate at the circuit. Reducing the 1/f noise, a correlative multi sampling and an autocorrelation method have been used, mainly. Nevertheless, a correlative multi sampling has a practical problem of limitation which is the band of applied frequency. Because of the problem, an autocorrelation method is used for the reducing of 1/f noise better than correlative multi sampling. General noise reduction filters along with the smoothing effect. In this study, the autocorrelation method based on adaptive algorithm is proposed to reduce the smoothing effect at the edge of image.
Adding SVC Spatial Scalability to Existing H.264/AVC Video
Authors: Ravin Sachdeva, Sumit Johar, Emiliano Piccinelli
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

This paper describes an innovative algorithm for adding SVC Spatial Scalability to all existing non-scalable H.264/AVC video streams. The algorithmic system builds on a full-decode-full-encode method of conversion and employs reuse of available data by an efficient downscaling of video information for different layers, thus reducing the complexity of the algorithm by manifold whilst maintaining a high coding efficiency. The complexity is further reduced by bypassing of various time consuming processes of the encoding process by the use of sharing and reuse of video information coming from original bitstream. Extensive analysis has been done to evaluate the gains in the coding efficiency and complexity of the algorithm using the full-decode-full-encode approach as a benchmark. The ultimate reduction in complexity is at least 60% from full-decode-full-encode while maintaining the output video quality. The modular nature of the algorithm is designed to be easily adaptable to other scalable video standards as well.
Mathematical modeling and efficient optimization methods for the distance-dependent rearrangement clustering problem
Authors: Scott R. Mcallister, Peter A. Dimaggio,  Jr., Christodoulos A. Floudas
Venue: Journal of Global Optimization (2009)

In this article we present a computational study for solving the distance-dependent rearrangement clustering problem using mixed-integer linear programming (MILP). To address sparse data sets, we present an objective function for evaluating the pair-wise interactions between two elements as a function of the distance between them in the final ordering. The physical permutations of the rows and columns of the data matrix can be modeled using mixed-integer linear programming and we present three models based on (1) the relative ordering of elements, (2) the assignment of elements to a final position, and (3) the assignment of a distance between a pair of elements. These models can be augmented with the use of cutting planes and heuristic methods to increase computational efficiency. The performance of the models is compared for three distinct re-ordering problems corresponding to glass transition temperature data for polymers and two drug inhibition data matrices. The results of the comparative study suggest that the assignment model is the most effective for identifying the optimal re-ordering of rows and columns of sparse data matrices.
Discriminative alignment training without annotated data for machine translation
Authors: Patrik Lambert, Rafael E. Banchs, Josep M. Crego
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)

In present Statistical Machine Translation (SMT) systems, alignment is trained in a previous stage as the translation model. Consequently, alignment model parameters are not tuned in function of the translation task, but only indirectly. In this paper, we propose a novel framework for discriminative training of alignment models with automated translation metrics as maximization criterion. In this approach, alignments are optimized for the translation task. In addition, no link labels at the word level are needed. This framework is evaluated in terms of automatic translation evaluation metrics, and an improvement of translation quality is observed.
Esfinge: a question answering system in the web using the web
Authors: Luís Fernando Costa
Venue: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations (2006)

Esfinge is a general domain Portuguese question answering system. It tries to take advantage of the great amount of information existent in the World Wide Web. Since Portuguese is one of the most used languages in the web and the web itself is a constantly growing source of updated information, this kind of techniques are quite interesting and promising.
Reading from Scratch --- A Vision-System for Reading Data on Micro-structured Surfaces
Authors: Ralf Dragon, Christian Becker, Bodo Rosenhahn, Jörn Ostermann
Venue: Proceedings of the 31st DAGM Symposium on Pattern Recognition (2009)

Labeling and marking industrial manufactured objects gets increasingly important nowadays because of novel material properties and plagiarism. As part of the Collaborative Research Center 653 which investigates micro-structured metallic surfaces for inherent mechanical data storage, we research into a stable and reliable optical readout of the written data. Since this comprises a qualitative surface reconstruction, we use directed illumination to make the micro structures visible. Then we apply a spectral analysis to obtain image partitioning and perform signal tracking enhanced by a customized Hidden Markov Model. In this paper, we derive the algorithms used and demonstrate reading data from a surface with 1.6kbit/cm2 from a micro-structured groove which varies by only 3μ m in depth (thus a "scratch"). We demonstrate the system's robustness with experiments with real and artificially-rendered surfaces.
Predicate projection in a bimodal spatial reasoning system
Authors: Samuel Wintermute, John E. Laird
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Spatial reasoning is a fundamental aspect of intelligent behavior, which cognitive architectures must address in a problem-independent way. Bimodal systems, employing both qualitative and quantitative representations of spatial information, are efficient and psychologically plausible means for spatial reasoning. Any such system must employ a translation from the qualitative level to the quantitative, where new objects (images) are created through the process of predicate projection. This translation has received little scrutiny. We examine this issue in the context of a bimodal spatial reasoning system integrated with a cognitive architecture (Soar). As part of this system, we define an expressive language for predicate projection that supports general and flexible image creation. We demonstrate this system on multiple spatial reasoning problems in the ORTS real-time strategy game environment.
Coal Enterprises Merger and Acquisition Risk Unascertained Clustering
Authors: Xiang Chen, Weihua Cai
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

Presently, China’s coal enterprises are in a merger and acquisition (M&A) phase environment. The coal enterprises in the process lack the risk control theoretical support. The paper built a coal enterprises M&A risk influence index system, using unascertained clustering method to analyze 2004-2008 coal enterprises M&A data. Given membership of samples belong to various types, the paper better resolved coal enterprises M&A risk classification problem.
Effects of Character Geometric Model on Perception of Sign Language Animation
Authors: Nicoletta Adamo-Villani, Ronnie Wilbur, Petra Eccarius, Laverne Abe-Harris
Venue: Proceedings of the 2009 Second International Conference in Visualisation (2009)

This paper reports a study that aimed to determine whether character geometric model (i.e. segmented vs.seamless) has an effect on how animated signing is perceived by viewers. Additionally, the study investigated whether the geometric model affects perception at varying degrees of linguistic complexity--specifically handshape complexity. We modeled and animated two polygonal 3D characters: Torrents,one seamless mesh, and Robby, a fully segmented avatar. Both characters had similar geometrical proportions, identical skeletal systems, similar visual styles and color schemes, and met standards of good character design. Each signed 60stimulus signs, divided into three groups—those with simple(group I), moderately complex (group II), and complex (groupIII) handshapes according to factors established in the linguistic literature. 53 participants, who learned ASL by age5, viewed animated clips in random order via web survey. They(1) identified the sign (if recognizable), and (2) rated its realism using a 5-point Likert scale. Findings show that the seamless avatar (Torrents) was rated highest, and simple handshapes were rated higher than moderately complex and complex ones.The interaction between character and handshape complexity was also significant. For Robby (more than for Torrents),ratings decreased as handshape complexity increased. The lower ratings for Robby could indicate a preference for seamless, deformable characters over segmented ones, especially in signs with complex handshapes.