ppxscal/embedding_network huggingface dataset:
Adobe ColdFusion 8 Web Application Construction Kit, Volume 2: Application Development, 1st edition
Authors: Ben Forta, Raymond Camden, Charlie Arehart, John C. Bland, Leon Chalnick, Ken Fricklas, Paul Hastings, Mike Nimer, Sarge Sargent, Robi Sen
Venue:  (2007)

ColdFusion 8 Web Application Construction Kit, Volume 2: Application Development begins by introducing important code organization and management techniques, and then progresses to topics that include integrating with all sorts of other technologies (including PDF, Adobe Flex, Ajax, advanced SQL and databases), debugging, and optimizing performance. From design and planning, to application deployment and troubleshooting, this instructional reference is all you need to successfully work, create, and progress with ColdFusion 8, the the most important ColdFusion since the product was created back in 1995
SQL and Relational Theory: How to Write Accurate SQL Code
Authors: C Date
Venue:  (2009)

Understanding SQL's underlying theory is the best way to guarantee that your SQL code is correct and your database schema is robust and maintainable. On the other hand, if you're not well versed in the theory, you can fall into several traps. In SQL and Relational Theory, author C.J. Date demonstrates how you can apply relational theory directly to your use of SQL. With numerous examples and clear explanations of the reasoning behind them, you'll learn how to deal with common SQL dilemmas, such as: Should database access granted be through views instead of base tables? Nulls in your database are causing you to get wrong answers. Why? What can you do about it? Could you write an SQL query to find employees who have never been in the same department for more than six months at a time? SQL supports "quantified comparisons," but they're better avoided. Why? How do you avoid them? Constraints are crucially important, but most SQL products don't support them properly. What can you do to resolve this situation? Database theory and practice have evolved since Edgar Codd originally defined the relational model back in 1969. Independent of any SQL products, SQL and Relational Theory draws on decades of research to present the most up-to-date treatment of the material available anywhere. Anyone with a modest to advanced background in SQL will benefit from the many insights in this book.
Active Model with Orthotropic Hyperelastic Material for Cardiac Image Analysis
Authors: Ken C. Wong, Linwei Wang, Pengcheng Shi
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

Meaningful physiological models are important for studying cardiac physiology. For cardiac image analysis, the models used should be detailed enough to describe the macroscopic physiological behaviors, but should not be too complicated for the inverse problems. To achieve this goal, we propose to use an orthotropic hyperelastic biomechanical model, which has only seven parameters but was reported as the best among the five tested well-known models in a comparative study. Combining with the active contraction forces provided by electromechanical models, the cyclic cardiac dynamics can be available to provide the physiological foundation for cardiac image analysis. To facilitate the complicated inverse problems, the system is implemented under the Cartesian coordinate system, and we propose the corresponding cardiac specific boundary conditions for anatomically realistic deformations. Experiments with analytical solutions were performed to verify the correctness of the implementation, and cardiac cycles were simulated to verify the physiological plausibility of the proposed model.
Circular choosability
Authors: Frédéric Havet, Ross J. Kang, Tobias Müller, Jean-Sébastien Sereni
Venue: Journal of Graph Theory (2009)

We study circular choosability, a notion recently introduced by Mohar and Zhu. First, we provide a negative answer to a question of Zhu about circular cliques. We next prove that cch(G)=O(ch(G)+ln|V(G)|) for every graph G. We investigate a generalization of circular choosability, the circular f-choosability, where f is a function of the degrees. We also consider the circular choice number of planar graphs. Mohar asked for the value of &tau;&thinsp;&colone;&thinsp;sup&lcub;cch(G)&thinsp;:&thinsp;G is planar&rcub;, and we prove that 6&le;&tau;&le;8, thereby providing a negative answer to another question of Mohar. We also study the circular choice number of planar and outerplanar graphs with prescribed girth, and graphs with bounded density. &copy; 2009 Wiley Periodicals, Inc. J Graph Theory 61: 241&ndash;270, 2009 The research in this paper was carried out while the second and third authors were doctoral research students at the University of Oxford and the last author was a doctoral research student at MASCOTTE.
A solution for an unified vision of the enterprise informations
Authors: Fabien Laniel, Mihaela Mathieu, Jean-Jacques Girardot
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

Search engines are now tools of every day life, Google being the most fa-mous example. While they allow to access easily Internet documents, they are more and more used, under the denomination of “enterprise search engines”, to manage the considerable amount of documents that constitute the memory of entreprises. We present the ground of a search engine that aims to propose a unified vision of the different documents formats (HTML, XML, Word, Mail, etc. but also data from databases) and to make search into these documents transparent to the user.
Inside risksReflections on Conficker
Authors: Phillip Porras
Venue: Communications of the ACM (2009)

An insider's view of the analysis and implications of the Conficker conundrum.
Deconstructing Network Attached Storage systems
Authors: Yuhui Deng
Venue: Journal of Network and Computer Applications (2009)

Network Attached Storage (NAS) has been gaining general acceptance, because it can be managed easily and files shared among many clients, which run different operating systems. The advent of Gigabit Ethernet and high speed transport protocols further facilitates the wide adoption of NAS. A distinct feature of NAS is that NAS involves both network I/O and file I/O. This paper analyzes the layered architecture of a typical NAS and the data flow, which travels through the layers. Several benchmarks are employed to explore the overhead involved in the layered NAS architecture and to identify system bottlenecks. The test results indicate that a Gigabit network is the system bottleneck due to the performance disparity between the storage stack and the network stack. The tests also demonstrate that the performance of NAS has lagged far behind that of the local storage subsystem, and the CPU utilization is not as high as imagined. The analysis in this paper gives three implications for the NAS, which adopts a Gigabit network: (1) The most effective method to alleviate the network bottleneck is increasing the physical network bandwidth or improving the utilization of network. For example, a more efficient network file system could boost the NAS performance. (2) It is unnecessary to employ specific hardware to increase the performance of the storage subsystem or the efficiency of the network stack because the hardware cannot contribute to the overall performance improvement. On the contrary, the hardware methods could have side effect on the throughput due to the small file accesses in NAS. (3) Adding more disk drives to an NAS when the aggregate performance reaches the saturation point can only contribute to storage capacity, but not performance. This paper aims to guide NAS designers or administrators to better understand and achieve a cost-effective NAS.
Quantification of Customer Multi-Preference and Motivation through Data and Text Mining in New Product Design
Authors: Xiang Li, Junhong Zhou, Wen Feng Lu
Venue: Proceeding of the 2006 conference on Integrated Intelligent Systems for Engineering Design (2006)

Effective collection and analysis of customer demand is a critical success factor for new product design and development. This chapter presents a set of customer requirement discovery methodologies to achieve broad and complex market studies for new products. The proposed approach uses data mining and text mining technologies to discover customer multi-preference and corresponding customer motivation. Using the proposed rule mining methodology, discovery rules can be flexibly defined, the complete customer multi-preference patterns are discovered and their statistic analysis of multi-preference can be conducted for new product design. With the proposed text mining methodology, the customer motivations are discovered and the percentage of surveyed customers with certain preference and the reason for this preference are presented. Combining the methodologies in text mining with rule mining, the customer motivations can be quantitatively described with statistic analysis results. A prototype system that allows on-line customer feedback collection, digitization of the language feedbacks, numerical descriptions of customer preferences and customer motivation of a product is developed to demonstrate the feasibility of the proposed methodologies. It is shown that the proposed work could significantly shorten the survey and analysis time for customer preference and is thus expected to help companies to reduce cycle time for new product design.
Pricing traffic in a spanning network
Authors: Hervé Moulin
Venue: Proceedings of the tenth ACM conference on Electronic commerce (2009)

Each user of the network needs to connect a pair of target nodes. There are no variable congestion costs, only a direct connection cost for each pair of nodes. A centralized mechanism elicits target pairs from users, and builds the cheapest forest meeting all demands. We look for cost sharing rules satisfying • Routing-proofness: no user can lower its cost by reporting as several users along an alternative path connecting his target nodes; • Stand Alone core stability: no group of users pay more than the cost of a subnetwork meeting all connection needs of the group. We construct first two core stable and routing-proof rules when connecting costs are all 0 or 1. One is derived from the random spanning tree weighted by the volume of traffic on each edge; the other is the weighted Shapley value of the Stand Alone cooperative game. For arbitrary connecting costs, we prove that the core is non empty if the graph of target pairs connects all pairs of nodes. Then we extend both rules above by the piecewise-linear technique. The former rule is computable in polynomial time, the latter is not.
Construction of Optimized Knowledge and New Knowledge Creation Support Tool
Authors: Akira Otsuki, Kenichi Okada
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

In this study, a tool was constructed that supports the process of trying to organize knowledge newly created after tacit knowledge has been optimized by applying knowledge management strategies, 3C, a marketing mix, and various enumeration methods. The tool was verified by quantitative methods, user feedback studies, and evaluation through comparison with similar tools. Until now, though some theories regarding the organization of newly created knowledge have been advocated based on user feedback studies, the method of concretely applying such theories to real-world business circumstances has not been presented. In the current study, the tool was tested through use in an actual administrative project and proved to be more effective than an already-existing tool used for the organization of newly-created knowledge.
Fault Diagnosis of Nonlinear Analog Circuits Using Neural Networks and Multi-Space Transformations
Authors: Yigang He, Wenji Zhu
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

A systematic approach, based on piece-wise linear (PWL) models, a bilinear transformation in multidimensional spaces and back-propagation neural networks (BPNN), for nonlinear analog fault diagnosis is proposed in this paper. The functions of input-output are applied for fault diagnosis to deal with the circuits without sufficient accessible nodes. Besides, we used the functions transformation in multi-space to select fault features, which can decrease the ambiguity groups and improve the performance of fault diagnosis. Through preprocessing of the signals of test nodes from the analog circuits, the optimal features are selected. These features are then fed into the BPNNs for fault location. The single fault diagnosis is mainly discussed in this paper. Finally, an illustration to demonstrate the strength of our proposed method is given.
A distributed constraint optimization approach for coordination under uncertainty
Authors: James Atlas
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Distributed Constraint Optimization (DCOP) provides a rich framework for modeling multi-agent coordination problems. We present a mapping to DCOP for large-scale team coordination problems that were used in the DARPA Coordinators program. We develop a new DCOP algorithm that scales to this domain and show that our algorithm out-performs other DCOP algorithms for this domain. Our approach is competitive with other general approaches used in the DARPA Coordinators program.
A New Method for Substation Planning Problem Based on Weighted K-Means
Authors: Wen Peng, Wenxia Liu
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Substation planning is considered the most important step in the power system planning process. It represents the main link between transmission and distribution system. In this paper, the substation planning problem is looked as a clustering process to divide all the loads into several clusters. The capacity of substation is estimated by the total value of loads. The location and links are solved iteratively using weighted k-means, whose objective function is the investment cost. Each cluster is charged by a substation which is in the cluster weighted center. The performance of the proposed method as compared to that of an evolutionary computing approach is promising.
Robust Human Detection under Occlusion by Integrating Face and Person Detectors
Authors: William Robson Schwartz, Raghuraman Gopalan, Rama Chellappa, Larry S. Davis
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Human detection under occlusion is a challenging problem in computer vision. We address this problem through a framework which integrates face detection and person detection. We first investigate how the response of a face detector is correlated with the response of a person detector. From these observations, we formulate hypotheses that capture the intuitive feedback between the responses of face and person detectors and use it to verify if the individual detectors' outputs are true or false. We illustrate the performance of our integration framework on challenging images that have considerable amount of occlusion, and demonstrate its advantages over individual face and person detectors.
Computationally Sound Formalization of Rerandomizable RCCA Secure Encryption
Authors: Yusuke Kawamoto, Hideki Sakurada, Masami Hagiya
Venue: Formal to Practical Security: Papers Issued from the 2005-2008 French-Japanese Collaboration (2009)

Rerandomizing ciphertexts plays an important role in protecting privacy in security protocols such as mixnets. We investigate the relationship between formal and computational approaches to the analysis of the security protocols using a rerandomizable encryption scheme. We introduce a new method of dealing with composed randomnesses in an Abadi-Rogaway-style pattern, formalize a rerandomizable RCCA secure encryption scheme, and prove its computational soundness.
Enhancing the Classroom Learning Experience with Web Lectures
Authors: Jason Day, Jim Foley, Remco Groeneweg, Charles van der Mast
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

In this paper, we present our vision and research results on the use of web lectures to enhance the classroom learning experience. By using web lectures to present lecture material in advance of class, more in-class time can be spent engaging students with authentic learning activities; our goal is to use class time for more learning by doing, less learning by listening. A pilot study has yielded promising results: hence we are further exploring this evolving concept.
Network survivability in large-scale regional failure scenarios
Authors: Bijan Bassiri, Shahram Shah Heydari
Venue: Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering (2009)

In this short paper we present a preliminary study of the impact of large-scale failures on communication networks. Models for study of large-scale failures are studied and unique characteristics of these scenarios as well as their differences with independent multiple-failure scenarios are presented. In particular, we focus on regional large-scale failure scenarios in which node/link failures are location-dependent. Methods for restoration of traffic and the issue of failure notification time are examined. The regional failure scenario is examined on a sample backbone European network and the simulation results including network capacity requirements and failure notification times for various cases are analyzed and discussed.
Emergence of Rules in Cell Assemblies of fLIF Neurons
Authors: Roman V. Belavkin Christian R. Huyck
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Inspired by biological cognition, CABOT project explores the ways symbolic processing can emerge in a system of neural cell assemblies (CAs). Here we show how a stochastic meta--control process can regulate learning of associations between the CAs, the neural basis of symbols. An experiment illustrates the learning between CAs representing conditions actions pairs, which leads to CA--based representations of 'if--then' rules.
Diffusion of Pedagogical Innovations as a Complex Adaptive Process --Agent-Based Modeling as Research Method
Authors: Jun-Song Huang, Manu Kapur
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

This paper is interested in both the sustainability and scalability of diffusion of pedagogical innovations in educational contexts. We argue that the diffusion of pedagogical innovations is a complex adaptive process. Current research methods, while informative, have limitations insofar as the non-linear, adaptive, and emergent properties of complex diffusion processes are concerned. To this end, this paper proposes the use of Agent-Based Modeling (ABM) as a complementary method. Following a review of existing methodologies, we set up an imperative for ABM, describe what ABM entails, and examine its affordances and limitations in emerging the diffusion patterns by simulating the decision making processes of boundedly-rational individuals in socio-organizational networks. We further argue that ABM is particularly helpful for exploring diffusion patterns in “what if” scenarios, and for making policies that foster sustainable and scalable innovation diffusion.
A Compute Unified System Architecture for Graphics Clusters Incorporating Data Locality
Authors: Christoph Müller, Steffen Frey, Magnus Strengert, Carsten Dachsbacher, Thomas Ertl
Venue: IEEE Transactions on Visualization and Computer Graphics (2009)

We present a development environment for distributed GPU computing targeted for multi-GPU systems, as well as graphics clusters. Our system is based on CUDA and logically extends its parallel programming model for graphics processors to higher levels of parallelism, namely, the PCI bus and network interconnects. While the extended API mimics the full function set of current graphics hardware—including the concept of global memory—on all distribution layers, the underlying communication mechanisms are handled transparently for the application developer. To allow for high scalability, in particular for network-interconnected environments, we introduce an automatic GPU-accelerated scheduling mechanism that is aware of data locality. This way, the overall amount of transmitted data can be heavily reduced, which leads to better GPU utilization and faster execution. We evaluate the performance and scalability of our system for bus and especially network-level parallelism on typical multi-GPU systems and graphics clusters.
Automated non-intrusive cargo inspection system using gamma-ray imaging (ROBOSCAN 1M)
Authors: Cristian Molder, Adrian Bîzgan, Emil Mieilica, Andrei Iacobita
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

Non-intrusive inspection of cargo containers has become a key issue in recent years to parry terrorist activities and to easily verify the shipping content at customs in order to avoid contraband. Such systems are mainly based on X- and gamma-ray radiography which offer inside images of the cargos. In this article we present a non-intrusive inspection system based on gamma-ray imaging called ROBOSCAN 1M. The system has a lower radiation field compared to existing X-ray systems, providing a smaller operational area and exclusion safety zone. It requires also less maintenance at a lower cost. It is also able to scan containers, vehicles, rail cars, while automatically detecting radioactive materials.
Efficient discovery of unusual patterns in time series
Authors: Stefano Lonardi, Jessica Lin, Eamonn Keogh, Bill Chiu
Venue: New Generation Computing (2007)

The problem of finding a specified pattern in a time series database (i.e., query by content) has received much attention and is now a relatively mature field. In contrast, the important problem of enumerating all surprising or interesting patterns has received far less attention. This problem requires a meaningful definition of "surprise", and an efficient search technique. All previous attempts at finding surprising patterns in time series use a very limited notion of surprise, and/or do not scale to massive datasets. To overcome these limitations we propose a novel technique that defines a pattern surprising if the frequency of its occurrence differs substantially from that expected by chance, given some previously seen data. This notion has the advantage of not requiring the user to explicitly define what is a surprising pattern, which may be hard, or perhaps impossible, to elicit from a domain expert. Instead, the user gives the algorithm a collection of previously observed "normal" data. Our algorithm uses a suffix tree to efficiently encode the frequency of all observed patterns and allows a Markov model to predict the expected frequency of previously unobserved patterns. Once the suffix tree has been constructed, a measure of surprise for all the patterns in a new database can be determined in time and space linear in the size of the database. We demonstrate the utility of our approach with an extensive experimental evaluation.
Kendall&#x2019;s correlation coefficient for vague preferences
Authors: Przemys&#x0142;aw Grzegorzewski
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2009)

The problem of measuring association between preference systems in situations with missing information or noncomparable outputs is discussed. New correlation coefficient, which generalizes Kendall&#x2019;s correlation coefficients used traditionally in statistics, is suggested. The construction utilizes IF-sets.