ppxscal/embedding_network huggingface dataset:
Beginning Java EE 6 Platform with GlassFish 3: From Novice to Professional, 1st edition
Authors: Antonio Goncalves
Venue:  (2009)

Sun's enterprise Java platform, Java EE (Enterprise Edition), is getting a facelift! Beginning Java EE 6 Platform with GlassFish 3 is one of the first tutorial books on the forthcoming Java EE 6 Platform. Stepbystep and easy to follow, this book describes many of the Java EE 6 specifications and reference implementations and shows them in action using practical examples. This book uses the new version of GlassFish 3 to deploy and administer the code examples. Written by an expert member of the Java EE 6 specification request and review board in the Java Community Process (JCP), this book contains the best information possible, from an expert's perspective in enterprise Java technologies and platform. What youll learn Get started with the new Java EE 6 Platform from Sun. Explore and use the new EJB 3.1 and JPA 2.0 APIs from entities to session beans to messagedriven beans, and more. Discover the new webtier development APIs including JSPs, JSTL, and Expression Language, and especially the new JSF 2.0 and Facelets. Uncover the new web services, RESTful services, and more available in Java EE 6. Create dynamic user interfaces for your enterprise and transactional Java applications. And more... Who is this book for? This book is suitable for advanced Java programmers as well as Java EE 6 beginners. Architects will also find information about how to layer their Java EE applications. About the Apress Beginning Series The Beginning series from Apress is the right choice to get the information you need to land that crucial entrylevel job. These books will teach you a standard and important technology from the ground up because they are explicitly designed to take you from novice to professional. Youll start your journey by seeing what you need to knowbut without needless theory and filler. Youll build your skill set by learning how to put together realworld projects step by step. So whether your goal is your next career challenge or a new learning opportunity, the Beginning series from Apress will take you thereit is your trusted guide through unfamiliar territory!
Unraveling the complexity of network management
Authors: Theophilus Benson, Aditya Akella, David Maltz
Venue: Proceedings of the 6th USENIX symposium on Networked systems design and implementation (2009)

Operator interviews and anecdotal evidence suggest that an operator's ability to manage a network decreases as the network becomes more complex. However, there is currently no way to systematically quantify how complex a network's design is nor how complexity may impact network management activities. In this paper, we develop a suite of complexity models that describe the routing design and configuration of a network in a succinct fashion, abstracting away details of the underlying configuration languages. Our models, and the complexity metrics arising from them, capture the difficulty of configuring control and data plane behaviors on routers. They also measure the inherent complexity of the reachability constraints that a network implements via its routing design. Our models simplify network design and management by facilitating comparison between alternative designs for a network. We tested our models on seven networks, including four university networks and three enterprise networks. We validated the results through interviews with the operators of five of the networks, and we show that the metrics are predictive of the issues operators face when reconfiguring their networks.
Modularities for bipartite networks
Authors: Tsuyoshi Murata
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

Real-world relations are often represented as bipartite networks, such as paper-author networks and event-attendee networks. Extracting dense subnetworks (communities) from bipartite networks and evaluating their qualities are practically important research topics. As the attempts for evaluating divisions of bipartite networks, Guimera and Barber propose bipartite modularities. This paper discusses the properties of these bipartite modularities and proposes another bipartite modularity that allows one-to-many correspondence of communities of different vertex types. Preliminary experimental results for the bipartite modularities are also described.
Simultaneous structure discovery and parameter estimation in gene networks using a multi-objective GP-PSO hybrid approach
Authors: Xinye Cai, Praveen Koduru, Sanjoy Das, Stephen M. Welch
Venue: International Journal of Bioinformatics Research and Applications (2009)

This paper presents a hybrid algorithm based on Genetic Programming (GP) and Particle Swarm Optimisation (PSO) for the automated recovery of gene network structure. It uses gene expression time series data as well as phenotypic data pertaining to plant flowering time as its input data. The algorithm then attempts to discover simple structures to approximate the plant gene regulatory networks that produce model gene expressions and flowering times that closely resemble the input data. To show the efficacy of the proposed approach, simulation results applied to flowering time control in Arabidopsis thaliana are demonstrated and discussed.
Using quantitative analysis to implement autonomic IT systems
Authors: Radu Calinescu, Marta Kwiatkowska
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

The software underpinning today's IT systems needs to adapt dynamically and predictably to rapid changes in system workload, environment and objectives. We describe a software framework that achieves such adaptiveness for IT systems whose components can be modelled as Markov chains. The framework comprises (i) an autonomic architecture that uses Markov-chain quantitative analysis to dynamically adjust the parameters of an IT system in line with its state, environment and objectives; and (ii) a method for developing instances of this architecture for real-world systems. Two case studies are presented that use the framework successfully for the dynamic power management of disk drives, and for the adaptive management of cluster availability within data centres, respectively.
CTL Model Update: Semantics, Computations and Implementation
Authors: Yulin Ding, Yan Zhang
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

Minimal change is a fundamental principle for modeling system dynamics. In this paper, we study the issue of minimal change for Computational Tree Logic (CTL) model update. We first propose five primitive operations which capture the basic update of the CTL model, and then define the minimal change criteria for CTL model update based on these primitive operations. We provide essential semantic and computational characterizations for our CTL model update approach. We develop a formal algorithm to implement this update that employs the underlying minimal change principle. We also present a CTL model update example using the well known microwave oven scenario.
Construction and Performance Evaluation of High Quality Curriculum Integrated with Information Technology
Authors: YouRu Xie, Rui Yin
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Based on the project 'Construction of High Quality Curriculum Integrated with Information Technology' undertaken by the author, this paper makes a detailed discussion on the original ideas, goals and contents, strategies and measures of the project as well. Meanwhile, this paper describes comprehensive performance evaluation in terms of the degree to which the project influenced on best-curriculum construction, teachers' professional development and students' learning abilities. The purpose of the paper is to provide beneficial references and experiences to facilitate the further curriculum construction and reform in universities.
Adaptive Fuzzy Logics for Contextual Hedge Interpretation
Authors: Stephan Waart Van Gulik
Venue: Journal of Logic, Language and Information (2009)

The article presents several adaptive fuzzy hedge logics. These logics are designed to perform a specific kind of hedge detection. Given a premise set Γ that represents a series of communicated statements, the logics can check whether some predicate occurring in Γ may be interpreted as being (implicitly) hedged by technically, strictly speaking or loosely speaking, or simply non-hedged. The logics take into account both the logical constraints of the premise set as well as conceptual information concerning the meaning of potentially hedged predicates (stored in the memory of the interpreter in question). The proof theory of the logics is non-monotonic in order to enable the logics to deal with possible non-monotonic interpretation dynamics (this is illustrated by means of several concrete proofs). All the adaptive fuzzy hedge logics are also sound and strongly complete with respect to their [0,1]-semantics.
Whetting the appetite of scientists: producing summaries tailored to the citation context
Authors: Stephen Wan, Cécile Paris, Robert Dale
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

The amount of scientific material available electronically is forever increasing. This makes reading the published literature, whether to stay up-to-date on a topic or to get up to speed on a new topic, a difficult task. Yet, this is an activity in which all researchers must be engaged on a regular basis. Based on a user requirements analysis, we developed a new research tool, called the Citation-Sensitive In-Browser Summariser (CSIBS), which supports researchers in this browsing task. CSIBS enables readers to obtain information about a citation at the point at which they encounter it. This information is aimed at enabling the reader to determine whether or not to invest the time in exploring the cited article further, thus alleviating information overload. CSIBS builds a summary of the cited document, bringing together meta-data about the document and a citation-sensitive preview that exploits the citation context to retrieve the sentences from the cited document that are relevant at this point. This paper briefly presents our user requirements analysis, then describes the system and, finally, discusses the observations from an initial pilot study. We found that CSIBS facilitates the relevancy judgment task, by increasing the users' self-reported confidence in making such judgements.
Detecting the Presence and Absence of Causal Relationships between Expression of Yeast Genes with Very Few Samples
Authors: Eun Yong Kang, Ilya Shpitser, Chun Ye, Eleazar Eskin
Venue: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (2009)

Inference of biological networks from high-throughput data is a central problem in bioinformatics. Particularly powerful for network reconstruction is data collected by recent studies that contain both genetic variation information and gene expression profiles from genetically distinct strains of an organism. Various statistical approaches have been applied to these data to tease out the underlying biological networks that govern how individual genetic variation mediates gene expression and how genes regulate and interact with each other. Extracting meaningful causal relationships from these networks remains a challenging but important problem. In this paper we use causal inference techniques to infer the presence or absence of causal relationships between yeast gene expressions in the framework of graphical causal models. We evaluate our method using a well studied dataset consisting of both genetic variation information and gene expressions collected over yeast strains. Our predictions of causal regulators are consistent with previously known experimental evidence. In addition, our method can distinguish between direct and indirect effects of variation on a gene expression level.
Error Estimation for Indoor 802.11 Location Fingerprinting
Authors: Hendrik Lemelson, Mikkel Baun Kjærgaard, Rene Hansen, Thomas King
Venue: Proceedings of the 4th International Symposium on Location and Context Awareness (2009)

802.11-based indoor positioning systems have been under research for quite some time now. However, despite the large attention this topic has gained, most of the research focused on the calculation of position estimates. In this paper, we go a step further and investigate how the position error that is inherent to 802.11-based positioning systems can be estimated. Knowing the position error is crucial for many applications that rely on position information: End users could be informed about the estimated position error to avoid frustration in case the system gives faulty position information. Service providers could adapt their delivered services based on the estimated position error to achieve a higher service quality. Finally, system operators could use the information to inspect whether a location system provides satisfactory positioning accuracy throughout the covered area. For position error estimation, we present four novel algorithms that take different features into account. Advantages of the combination of these four algorithms are explored by using a machine-learning approach. We evaluate our proposed algorithms in two different real-world deployments by using real-world data and emulation. The results show that our algorithms work independently of the environment and the positioning algorithm, and with an average precision for estimating the position error of up to 1.45 meters. The algorithms can --- by adjusting parameters --- realize different tradeoffs between underestimating and overestimating errors. Furthermore we comment on the algorithms' space and time complexity.
Design of a relaying electroosmosis pump driven by low-voltage DC
Authors: Qiuquan Guo, Yu Liu, Xueyin Wu, Jun Yang
Venue: Microsystem Technologies (2009)

Electroosmosis pumps (EOPs) have been widely used for manipulating small amounts of reagents for chemical and biological analysis. Traditionally, a high-voltage DC has to be applied in order to achieve the required flow rate. One alternative is to use low AC voltage. Here we propose another solution, which, instead of using a high-voltage DC or low AC voltage, adds a low-voltage DC to an array of electrodes. This design of EOP is called a relaying EOP or cascade EOP. In this study, we intend to push the limit of the low-voltage further down to 2&#x00a0;V by patterning a dense electrode array in a straight microchannel. Two patterns of interdigitated electrodes, symmetric with equal size electrodes and asymmetric with unequal size electrodes, are proposed. Simulations are performed to optimize the distribution and geometrical parameters of the electrode array in order to achieve the maximum flow rate. The proposed low-voltage DC electroosmosis pump shows an advantage in integrating EOP into portable Lab-on-a-chip devices. In addition, the low-voltage DC EOP shows a good promise for in vivo biomedical applications such as drug delivery.
The senior companion: a semantic web dialogue system
Authors: Debora Field, Roberta Catizone, WeiWei Cheng, Alexiei Dingli, Simon Worgan, Lei Ye, Yorick Wilks
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

The Senior Companion (SC) is a fully implemented Windows application intended for intermittent use by one user only (a senior citizen) over potentially many years. The thinking behind the SC is to make a device that will give its owner comfort, company, entertainment, and some practical functions. The SC will typically be installed at home, either as an application on a personal computer, or on a dedicated device (like a Chumby) or an intelligent coffee table (like Microsoft's Surface). By means of multimodal input and output, and a graphical interface, the SC provides its 'owner' with different functionalities, which currently include: &bull; conversing with the user about his personal photos &bull; learning about the user, user's family, and life history &bull; telling the user jokes &bull; reading the news (via RSS feed from the internet)
A meta-level evolutionary strategy for many-criteria design: Application to improving tracking filters
Authors: I. J. Dotu, J. García, A. Berlanga, J. M. Molina
Venue: Advanced Engineering Informatics (2009)

We present a novel meta-level heuristic algorithm for multi-criteria search. It focuses on dynamically adapting the optimization criteria through the set of active objectives instead of using the evolutionary strategy (ES) parameters as other meta-level approaches do. The meta-level ES dynamically searches for the subset of objectives that achieves the best global performance. It assumes that the active subset can represent the real structure of the trade-off surface and consider all objectives at the same time as a pure multi-objective evolutionary approach (MOEA) would do. We have successfully applied this heuristic to improve the efficiency of tracking filters design, a real-world problem requiring effective and fast optimization techniques. Our approach yields competitive results and drastically reduces the computational cost. The results show an important advantage in efficiency with respect to previous conventional approaches for applying evolutionary algorithms (EA) to the same design problem. The proposed technique can be applied to real-world problems with a high number of active dependent objectives, a frequent occurrence in engineering design.
Stochastic power/ground supply voltage prediction and optimization via analytical placement
Authors: Andrew B. Kahng, Bao Liu, Qinke Wang
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

Increasingly significant power/ground (P/G) supply voltage degradation in nanometer VLSI designs leads to system performance degradation and even malfunction, which requires stochastic analysis and optimization techniques. We represent the supply voltage degradation at a P/G node as a function of the supply currents and the effective resistance of a P/G supply network and propose an efficient stochastic system-level P/G supply voltage prediction method, which computes P/G supply network effective resistances in a random walk process. We further propose to reduce P/G supply voltage degradation via placement of supply current sources, and integrate P/G supply voltage degradation reduction with conventional placement objectives in an analytical placement framework. Our experimental results show that the proposed stochastic P/G supply network prediction method achieves 10×-100× speedup compared with traditional SPICE simulation, and the proposed P/G supply voltage degradation aware placement achieves an average of 20.9% (11.7%) reduction on maximum (average) supply voltage degradation with only 4.3 % wirelength increase.
A distributed Key Message algorithm to optimize the communication in clusters
Authors: Yang Wang, Ming Zhu, Hua Li
Venue: Parallel Computing (2009)

The Key Message (KM) approach prioritizes communications along the critical path to speed up the execution of parallel applications in a cluster environment. However, the current KM approaches (i.e, the Static KM (SKM) and the dynamic KM with a central predictor (CDKM)) either lack the capability of adapting to dynamic environment or suffer from the expensive centralized control to predict dynamic critical path rendering them to be suboptimal. In this paper, we introduce a dynamic and distributed KM algorithm (DDKM) that takes this dynamic nature into account while avoiding overheads of central control, thus, overcoming the drawbacks of its predecessors. To evaluate the DDKM algorithm, we implement it and simulate it in a cluster environment whose communication network (e.g., shared bus) can be modeled as an M/D/1. We compare DDKM with current KM approaches. The performance of DDKM is close to that of CDKM, and much better than SKM up to 28.9% when the network is highly congested. These results demonstrate that DDKM is a promising optimization in a real cluster environment.
Growing models from deterministic to random hierarchical networks
Authors: Juan Zhang, Huan Huang
Venue: International Journal of Systems, Control and Communications (2009)

In this paper, we introduce a growing hierarchical network model with a tunable parameter q which is an economic model based on the real-life networks of profit distributions. Our theoretical results indicate that the model follows a power-law degree distribution P(k) &prop; k&lt;SUP align=right&gt;&minus;&gamma;&lt;/SUP&gt; with the power-law exponent of &gamma; &asymp; 1. Besides, the model has a smaller Average Path Length (APL) and a larger clustering coefficient for smaller q, proved to be a Small-World Network (SWN).
LISA: Image Compression Scheme Based on an Asymmetric Hierarchical Self-Organizing Map
Authors: Cheng-Fa Tsai, Yu-Jiun Lin
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

A Kohonen network, also called Self-Organizing Map (SOM), is a competitive learning network, and is appropriate for solving an image compression problem owing to its ability to generate high-quality compressed images. However, SOM has a large computation cost, making it impractical due to a lengthy training process. Hence, the Hierarchical Self-Organizing Map (HSOM) had been presented and found to reduce computation cost. Although a hierarchical architecture speeds up SOM, HSOM is still not practical enough because of a high compression cost. Therefore, this investigation employs a hybrid scheme to increase the efficiency and effectiveness of HSOM. Simulation results reveal that the proposed algorithm is much more efficient and effective than other algorithms, such as LBG, SOM, and HSOM.
Image Analysis by Modified Krawtchouk Moments
Authors: Luo Zhu, Jiaping Liao, Xiaoqin Tong, Li Luo, Bo Fu, Guojun Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

In the paper, a set of modified Krawtchouk moments with high accuracy and computational speed is introduced. Three computational aspects of Krawtchouk moments, which are weighted and normalized Krawtchouk polynomials, symmetry and recurrence relation, are discussed respectively. Firstly, by normalizing the Krawtchouk polynomials with the weight functions and norms, the values of the polynomials are limited to a smaller range than those of the classical polynomials. Secondly, three symmetrical properties are used to simplify the computational complexities of the high-order moments by reducing the modified polynomials by a factor of eight and lower the highest order of the calculated polynomials from N to N/2 ¿ 1. Thirdly, the classical recursive relations are modified to calculate the normalized polynomials when the order N goes larger. Finally, the paper demonstrates the effectiveness of the proposed moments by using the method of image reconstruction.