ppxscal/embedding_network huggingface dataset:
Beginning Microsoft SQL Server 2008 Administration
Authors: Chris Leiter, Dan Wood, Michael Cierkowski, Albert Boettger
Venue:  (2009)

SQL Server 2008 introduces many new features that will change database administration procedures; many DBAs will be forced to migrate to SQL Server 2008. This book teaches you how to develop the skills required to successfully administer a SQL Server 2008 database; no prior experience is required. The material covers system installation and configuration/architecting, implementing and monitoring security controls, configuring and managing network communications, automating administration tasks, disaster prevention and recovery, performance monitoring, optimizing and ensuring high availability, as well as major SQL Server 2008 components including Integration Services, Reporting Services, Analysis Services, and Service Broker.
Automatic Quantification of Fluorescence from Clustered Targets in Microscope Images
Authors: Harri Pölönen, Jussi Tohka, Ulla Ruotsalainen
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

A cluster of fluorescent targets appears as overlapping spots in microscope images. By quantifying the spot intensities and locations, the properties of the fluorescent targets can be determined. Commonly this is done by reducing noise with a low-pass filter and separating the spots by fitting a Gaussian mixture model with a local optimization algorithm. However, filtering smears the overlapping spots together and lowers quantification accuracy, and the local optimization algorithms are uncapable to find the model parameters reliably. In this sudy we developed a method to quantify the overlapping spots accurately directly from the raw images with a stochastic global optimization algorithm. To evaluate the method, we created simulated noisy images with overlapping spots. The simulation results showed the developed method produced more accurate spot intensity and location estimates than the compared methods. Microscopy data of cell membrane with caveolae spots was also succesfully quantified with the developed method.
Real-Time Volumetric Reconstruction and Tracking of Hands in a Desktop Environment
Authors: Christoph John, Ulrich Schwanecke, Holger Regenbrecht
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

A probabilistic framework for vision based volumetric reconstruction and marker free tracking of hand and face volumes is presented, which exclusively relies on off-the-shelf hardware components and can be applied in standard office environments. Here a 3D reconstruction of the interaction environment (user-space) is derived from multiple camera viewpoints which serve as input sources for mixture particle filtering to infer position estimates of hand and face volumes. The system implementation utilizes graphics hardware to comply with real-time constraints on a single desktop computer.
Thermo-mechanical FEM Analysis on Crack Prediction of Solidified Shell in Funnel-Shaped Mold
Authors: Xin Jin, Tingzhi Rng, Jie Guan
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

In this paper, a 3-dimensional mathematical model has been developed for the thermo-mechanical coupled analysis of the solidification process of carbon steel in funnelshaped mold using thermo-elastic-plastic finite element method (FEM). The major application of the model is to perform computations of temperature, stress and longitudinal cracking index (LCI) variations in shell. The effects of casting speed on stress and LCI are discussed. The results show that the temperature at the thin slab off-corner of wide face is higher than the temperature at the center of the wide face and narrow face, the temperature history at the thin slab off-corner appears two plateaus at 280mm and 840mm below meniscus, and the peak stress of solidification shell occurs at the region of funnel edge, where the shell has high cracking susceptibility. The LCI is high at the wideface center, funnel edge and off-corner of thin slab wide face. Increasing casting speed within certain range can decrease the LCI of original shell and reduce the possibility of longitudinal crack.
xDUCON: Cross Domain Usage Control through Shared Data Spaces
Authors: Giovanni Russello, Naranker Dulay
Venue: Proceedings of the 2009 IEEE International Symposium on Policies for Distributed Systems and Networks (2009)

In this paper, we present a preliminary design of a framework for coordinating and enforcing usage control policies across different collaborating organizations. We named our framework xDUCON. The main goal of xDUCON is the specification of usage control policies that concisely capture conditions, authorizations, and obligations on both providers and consumers of resources. The novelty of xDUCON is its enforcement design that is based on the Shared Data Space (SDS) abstraction. The SDS allows the coordination of the decision and enforcement points abstracting from the details of the actual deployment of the framework. Moreover, the SDS abstraction caters for the necessary synchronization facilities necessary to realize a concrete implementation of control usage framework such as support for entity mutability and control over long-lived sessions to evaluate the access rights of a subject while the access is being executed.
Detecting Projected Outliers in High-Dimensional Data Streams
Authors: Ji Zhang, Qigang Gao, Hai Wang, Qing Liu, Kai Xu
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

In this paper, we study the problem of projected outlier detection in high dimensional data streams and propose a new technique, called Stream Projected Ouliter deTector (SPOT), to identify outliers embedded in subspaces. Sparse Subspace Template (SST), a set of subspaces obtained by unsupervised and/or supervised learning processes, is constructed in SPOT to detect projected outliers effectively. Multi-Objective Genetic Algorithm (MOGA) is employed as an effective search method for finding outlying subspaces from training data to construct SST. SST is able to carry out online self-evolution in the detection stage to cope with dynamics of data streams. The experimental results demonstrate the efficiency and effectiveness of SPOT in detecting outliers in high-dimensional data streams.
Ants and reinforcement learning: a case study in routing in dynamic networks
Authors: Devika Subramanian, Peter Druschel, Johnny Chen
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

We investigate two new distributed routing algorithms for data networks based on simple biological "ants" that explore the network and rapidly learn good routes, using a novel variation of reinforcement learning. These two algorithms are fully adaptive to topology changes and changes in link costs in the network, and have space and computational overheads that are competitive with traditional packet routing algorithms: although they can generate more routing traffic when the rate of failures in a network is low, they perform much better under higher failure rates. Both algorithms are more resilient than traditional algorithms, in the sense that random corruption of routing state has limited impact on the computation of paths. We present convergence theorems for both of our algorithms drawing on the theory of non-stationary and stationary discrete-time Markov chains over the reals. We present an extensive empirical evaluation of our algorithms on a simulator that is widely used in the computer networks community for validating and testing protocols. We present comparative results on data delivery performance, aggregate routing traffic (algorithm overhead), as well as the degree of resilience for our new algorithms and two traditional routing algorithms in current use. We also show that the performance of our algorithms scale well with increase in network size-using a realistic topology.
On the Consistency of Bayesian Variable Selection for High Dimensional Linear Models
Authors: Shuyun Wang, Yihui Luan
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

First, good performance of Bayesian variable selection (BVS for short) in a variety of applications is introduced. Then, we will give a theoretical explanation why BVS works so well in linear models. We assume the true regression coefficients vector of the linear model is sparsity, in a sense that some regression coefficients are bounded from zero while the rest are exactly zero. In this case, under some conditions, BVS will show it can select the true model by means of giving a consistent estimate of the true regression coefficients vector.
Intelligent assistance for teachers in collaborative e-learning environments
Authors: Agustin Casamayor, Analia Amandi, Marcelo Campo
Venue: Computers Education (2009)

Collaborative learning environments provide a set of tools for students acting in groups to interact and accomplish an assigned task. In this kind of systems, students are free to express and communicate with each other, which usually lead to collaboration and communication problems that may require the intervention of a teacher. In this article, we introduce an intelligent agent approach to assist teachers through monitoring participations made by students within a collaborative distance learning environment, detecting conflictive situations in which a teacher's intervention may be necessary. High precision rates achieved on conflict detection scenarios suggest great potential for the application of the proposed rule-based approach for providing personalized assistance to teachers during the development of group works.
From Machine Learning to Child Learning
Authors: Charles Ling
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

Machine Learning endeavors to make computers learn and improve themselves over time. It is originated from analyzing human learning, and is now maturing as computers can learn more effectively than human for many specific tasks, such as adaptive expert systems and data mining. The effective and fruitful research in machine learning can now be used to improve our thinking and learning, especially for our children. In this talk, I will discuss my efforts in using machine learning (and AI) for child education in Canada and China. In early 2009, I hosted a TV series in a major talk show in China. The impact of such work in China and around the world can be huge.
Networks of Evolutionary Picture Processors with Filtered Connections
Authors: Paolo Bottoni, Anna Labella, Florin Manea, Victor Mitrana, Jose M. Sempere
Venue: Proceedings of the 8th International Conference on Unconventional Computation (2009)

In this paper we simplify the model of computation considered in [1], namely network of evolutionary picture processors, by moving the filters from the nodes to the edges. Each edge is now viewed as a two-way channel such that input and output filters, respectively, of the two nodes connected by the edge coincide. Thus, the possibility of controlling the computation in such networks seems to be diminished. In spite of this observation all the results concerning the computational power of networks of evolutionary picture processors reported in [1] are extended over these simplified networks.
Simulation of the Growth Process of a Silicium Nanotubes Structure as Biomaterial in the Porozity of Zeolite AFI
Authors: Ana Ioanid, Radu Mircea Ciuceanu
Venue: Proceedings of the 2008 First International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing (2008)

Hydroxyapatite (HA,Ca10(PO4)6(OH)2), that the principal mineral component of the bone tissue, has remarkable precursor of growth properties in the porous structure sort with strongly interconnected pores. The interconnection of the pores is an essential condition assuring high quality of bone implants. We suggest the experimentation of a silicon nanotubes structure (SiNT) as support to enhance the growth of a high quality HA. We propose a model obtaining a silicon nanotubes structure, by silicon atoms adsorption, from vapour phase, in the pores of AlPO4 (AFI) zeolite. A collection of 3D interconnected nanotubes of the deposited silicium can be obtained after matrix removal.
Fast Determination of Sensitivity in the Presence of Countermeasures in BOWS-2
Authors: Andreas Westfeld
Venue: Information Hiding: 11th International Workshop, IH 2009, Darmstadt, Germany, June 8-10, 2009, Revised Selected Papers (2009)

The second Break Our Watermarking System (BOWS-2) contest exposed a watermarking algorithm named Broken Arrows (BA) to worldwide attacks. In its second episode, the previously existing daily limit of 30 oracle calls per IP address was lifted to allow for sensitivity analysis. Often disrespected because of their extensive oracle use, sensitivity attacks can reveal up to one bit of information about the watermark in each experiment. In this paper we describe how we circumvented BA's countermeasures against sensitivity attacks.
A Case Study of Variation Mechanism in an Industrial Product Line
Authors: Pengfei Ye, Xin Peng, Yinxing Xue, Stan Jarzabek
Venue: Proceedings of the 11th International Conference on Software Reuse: Formal Foundations of Reuse and Domain Engineering (2009)

Fudan Wingsoft Ltd. developed a product Line of Wingsoft Financial Management Systems (WFMS-PL) providing web-based financial services for employees and students at universities in China. The company used a wide range of variation mechanisms such as conditional compilation and configuration files to manage WFMS variant features. We studied this existing product line and found that most variant features had fine-grained impact on product line components. Our study also showed that different variation mechanisms had different, often complementary, strengths and weaknesses, and their choice should be mainly driven by the granularity and scope of feature impact on product line components. We hope our report will help companies evaluate and select variation mechanisms when moving towards the product line approach.
On the efficient classification of data structures by neural networks
Authors: Paolo Frasconi, Marco Gori, Alessandro Sperduti
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

In the last few years it has been shown that recurrent neural networks are adequate for processing general data structures like trees and graphs, which opens the doors to a number of new interesting applications previously unexplored. In this paper, we analyze the efficiency of learning the membership of DO AGs (Directed Ordered Acyclic Graphs) in terms of local minima of the error surface by relying on the principle that their absence is a guarantee of efficient learning. We give sufficient conditions under which the error surface is local minima free. Specifically, we define a topological index associated with a collection of DOAGs that makes it possible to design the architecture so as to avoid local minima.
Search space reduction and Russian Doll search
Authors: Kenil K. C. Cheng, Roland H. C. Yap
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

In a constraint optimization problem (COP), many feasible valuations lead to the same objective value. This often means a huge search space and poor performance in the propagation between the objective and problem variables. In this paper, we propose a different modeling and search strategy which focuses on the cost function. We show that by constructing a dual model on the objective variables, we can get strong propagalion between the objective variables and the problem variables which allows search on the objective variables. We explain why and when searching on the objective variables can lead to large gains. We present a new Russian Doll Search algorithm, ORDS, which works on objective variables with dynamic variable ordering. Finally, we demonstrate using the hard Still-Life optimization problem the benefits of changing to the objective function model and ORDS.
Analyzing scheduling in the food-processing industry: structure and tasks
Authors: Renzo Akkerman, Dirk Pieter van Donk
Venue: Cognition, Technology and Work (2009)

Production scheduling has been widely studied in several research areas, resulting in a large number of methods, prescriptions, and approaches. However, the impact on scheduling practice seems relatively low. This is also the case in the food-processing industry, where industry-specific characteristics induce specific and complex scheduling problems. Based on ideas about decomposition of the scheduling task and the production process, we develop an analysis methodology for scheduling problems in food processing. This combines an analysis of structural (technological) elements of the production process with an analysis of the tasks of the scheduler. This helps to understand, describe, and structure scheduling problems in food processing, and forms a basis for improving scheduling and applying methods developed in literature. It also helps in evaluating the organisational structures and information flows related to scheduling.
Active Structured Learning for High-Speed Object Detection
Authors: Christoph H. Lampert, Jan Peters
Venue: Proceedings of the 31st DAGM Symposium on Pattern Recognition (2009)

High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system that can adapt to arbitrary objects and a wide range of lighting conditions is a challenging problem, especially if hard real-time constraints apply like in robotics scenarios. In this work, we introduce a method for learning a discriminative object tracking system based on the recent structured regression framework for object localization. Using a kernel function that allows fast evaluation on the GPU, the resulting system can process video streams at speed of 100 frames per second or more.Consecutive frames in high speed video sequences are typically very redundant, and for training an object detection system, it is sufficient to have training labels from only a subset of all images. We propose an active learning method that select training examples in a data-driven way, thereby minimizing the required number of training labeling. Experiments on realistic data show that the active learning is superior to previously used methods for dataset subsampling for this task.
A clique-covering sufficient condition for hamiltonicity of graphs
Authors: Alain Bretto, Thierry Vallée
Venue: Information Processing Letters (2009)

A graph is hamiltonian if it contains a cycle which goes through all vertices exactly once. Determining if a graph is hamiltonian is known as NP-complete problem and no satisfactory characterization for hamiltonian graphs has been found. There are several necessary conditions for hamiltonicity and since the seminal work of Dirac in 1952, many sufficient conditions were found. These conditions are usually expressed in terms of node degree, connectivity, density, toughness, independent sets, regularity and forbidden subgraphs. In this article we give an extended clique decomposition condition ensuring the hamiltonicity of a large class of graphs. Then we discuss briefly the possibility of broader extensions as well as algorithmic issues.
Embedding Linear-Time Temporal Logic into Infinitary Logic: Application to Cut-Elimination for Multi-agent Infinitary Epistemic Linear-Time Temporal Logic
Authors: Norihiro Kamide
Venue: Computational Logic in Multi-Agent Systems: 9th International Workshop, CLIMA IX, Dresden, Germany, September 29-30, 2008. Revised Selected and Invited Papers (2009)

Linear-time temporal logic (LTL) is known as one of the most useful logics for verifying concurrent systems, and infinitary logic (IL) is known as an important logic for formalizing common knowledge reasoning. The research fields of both LTL and IL have independently been developed each other, and the relationship between them has not yet been discussed before. In this paper, the relationship between LTL and IL is clarified by showing an embedding of LTL into IL. This embedding shows that globally and eventually operators in LTL can respectively be represented by infinitary conjunction and infinitary disjunction in IL. The embedding is investigated by two ways: one is a syntactical way, which is based on Gentzen-type sequent calculi, and the other is a semantical way, which is based on Kripke semantics. The cut-elimination theorems for (some sequent calculi for) LTL, an infinitary linear-time temporal logic ILT ¿ (i.e., an integration of LTL and IL), a multi-agent infinitary epistemic linear-time temporal logic IELT ¿ and a multi-agent epistemic bounded linear-time temporal logic ELT l are obtained as applications of the resulting embedding theorem and its extensions and modifications. In particular, the cut-elimination theorem for IELT ¿ gives a new proof-theoretical basis for extremely expressive time-dependent multi-agent logical systems with common knowledge reasoning. 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
Human Control Modeling Based on Multimodal Sensory Feedback Information
Authors: Edwardo Murakami, Toshihiro Matsui
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

In order to simulate the human control behavior during a manipulation task in a remote controlled or in a X-by-wire systems, first it is necessary to measure and analyze the human control characteristics. The aim of this research is to measure the operator reaction time and analyze the human visual and force sensory feedback integration related to a manipulation task. Using the developed master-slave type experimental device it was possible to identify and build a human operator control model related to different sensory feedback. The human model related to visual feedback solely and visual/force feedback was identified using the techniques of system identification methods.
IPv6 Label Switching on IEEE 802.15.4
Authors: Udo Payer, Stefan Kraxberger, Peter Holzer
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

Driven by the idea to converge to the Internet of Things, we searched within the course of a FP6-project for a suitable mechanism to transport IP packets on ad-hoc wireless personal area networks (WPANs). Prior work was already done and so we decided to start with RFC4944, which was probably the best working solutions for this problem. But since the design of RFC4944 was only targeted to a point-to-point transport of IPv6 packets via IEEE 802.15.4, we missed routing- and power-management capabilities. Therefore, we reassessed RFC4944 and as a result, this paper describes an ”intuitive approach” to transport IPv6-packet on Zigbee-based WPANs. The basic idea of the proposed solution is the sole usage of inherent IPv6-mechanisms (without the help of additional container or frames) and the usage of existing routing- and fragmentation- capabilities. In this paper we describe an IPv6-based WPAN-implementation, which can keep up with the small packet overheat of RFC4944, and which was extended by routing and power management capabilities. Additionally, a mechanism was added to replace the ”expensive” packet forwarding mechanism by a fast and efficient label-switching technique. This mechanisms can help to reduce the switching table size but also the size of the IP packet headers.