ppxscal/embedding_network huggingface dataset:
The Iterated Restricted Immediate Snapshot Model
Authors: Sergio Rajsbaum, Michel Raynal, Corentin Travers
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

In the Iterated Immediate Snapshot model (${\mathit{IIS}}$) the memory consists of a sequence of one-shot Immediate Snapshot ($\mathit{IS}$) objects. Processes access the sequence of $\mathit{IS}$ objects, one-by-one, asynchronously, in a wait-free manner; any number of processes can crash. Its interest lies in the elegant recursive structure of its runs, hence of the ease to analyze it round by round. In a very interesting way, Borowsky and Gafni have shown that the ${\mathit{IIS}}$ model and the read/write model are equivalent for the wait-free solvability of decision tasks.This paper extends the benefits of the $\mathit{IIS}$ model to partially synchronous systems. Given a shared memory model enriched with a failure detector, what is an equivalent $\mathit{IIS}$ model? The paper shows that an elegant way of capturing the power of a failure detector and other partially synchronous systems in the ${\mathit{IIS}}$ model is by restricting appropriately its set of runs, giving rise to the Iterated Restricted Immediate Snapshot model ($\mathit{IRIS}$).
Dynamic Architectures: Problems and Solutions
Authors: S. I. Kartashev
Venue: Computer (1978)

A standardizable LSI microprocessor with on-chip configuration control directed by operating-system commands promises a series of computer sets dynamically matched to user-program characteristics.
Adaptive Star Grammars for Graph Models
Authors: Frank Drewes, Berthold Hoffmann, Mark Minas
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

Adaptive star grammars generalize well-known graph grammar formalisms based on hyperedge and node replacement while retaining, e.g., parseability and the commutativity and associativity of rule application. In this paper, we study how these grammars can be put to practical use for the definition of graph models. We show how to use adaptive star grammars to specify program graphs, models of object-oriented programs that have been devised for investigating refactoring operations. For this, we introduce notational enhancements and one proper extension (application conditions). The program graphs generated by the grammar comprise not only the nested composition of entities, but also scope rules for their declarations. Such properties cannot easily be defined by meta-models like Uml class diagrams. In contrast, adaptive star grammars cover several aspects of class diagrams.
Empirical Analysis of the Relation between Level of Detail in UML Models and Defect Density
Authors: Ariadi Nugroho, Bas Flaton, Michel R. Chaudron
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

This paper investigates the relation between the level of detail (LoD) in UML models and defect density of the associated implementation. We propose LoD measures that are applicable to both class- and sequence diagrams. Based on empirical data from an industrial software project we have found that classes with higher LoD, calculated using sequence diagram LoD metrics, correlates with lower defect density. Overall, this paper discusses a novel and practical approach to measure LoD in UML models and describes its application to a significant industrial case study.
Beginning C# 2008 XXXXXXXXXXXXX, 2 edition
Authors: Christian Gross
Venue:  (2008)

This book is for anyone who wants to write good C# codeeven if you have never programmed before. Writing good code can be a challengethere are so many options, especially in a .NET language like C#. If you want to really get the best from a programming language, you need to know which features work best in which situations and understand their strengths and weaknesses. It is this understanding that makes the difference between coding and coding well. Beginning C# 2008: From Novice to Professional, Second Edition has been written to teach you how to use the C# programming language to solve problems. From the earliest chapters, and from the first introductory concepts, youll be looking at realworld programming challenges and learning how C# can be used to overcome them. As you progress through the book, the problems become more involved and interesting, while the solutions become correspondingly more complex and powerful as C# features interact to achieve the results that you want. This second edition has been revised and improved to now include the latest SQL Server 2008 release and explain how you can integrate SQL Server 2008 with your C# applications. By the time youve finished reading this book and worked through the sample exercises, youll be a confident and very competent C# programmer. You will still have many explorations of the .NET Framework API to look forward to, but you will have a firm foundation to build from, and you will know exactly where to go to find the things that you need to progress confidently in your projects. What youll learn Everything to get you started with C# 2008 from scratchfrom installing the tools to writing your first applications. The core concepts of .NET 3.5 programming: from decision trees to data structures, from exceptions to lambda expressions, and from objects to components. Learn what LINQ is, why functional programming can be important, how generics make your life easier, and much, much, more! Who is this book for This book is for anyone whos just starting out to learn about C#. It doesnt assume any prior knowledge of objectoriented programming, of the .NET Framework, or of coding in general. It simply assumes that youre an intelligent person who wants to learn and starts the journey from there. 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!
CMIC at INEX 2007: Book Search Track
Authors: Walid Magdy, Kareem Darwish
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

With massive book digitization efforts underway, the need for effective retrieval of books and pages in books is an important problem. This paper describes our submissions to the INEX 2007 Book Search track. We explored using book specific features such as table of content and index pages and headers along with non-book specific features. Our results show that indexing the entire contents of books and headers provided the most effective retrieval strategy.
Gear Fault Diagnosis by Using Wavelet Neural Networks
Authors: Y. Kang, C. C. Wang, Y. P. Chang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Fault diagnosis in gear train system is important in order to transmitting power effectively. The artificial intelligent such as neural network is widely used in fault diagnosis and already substituted for traditional methods such as kurtosis method, time analysis and so on. The symptoms of vibration signals in frequency domains have been used as inputs to the neural network and diagnosis results are obtained by network computation. This study presents gear fault diagnosis by using wavelet neural networks (WNN) and Morlet wavelet is used as the activation function in hidden layer of back-propagation neural networks (BPNN). Furthermore, the diagnosis results are compared within both methods of WNN and BPNN in four gear cases.
MIS-PyME Software Measurement Maturity Model-Supporting the Definition of Software Measurement Programs
Authors: María Díaz-Ley, Félix García, Mario Piattini
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

An important reason why measurement program implementation fails is that the maturity of companies as regards measurement has not been taken into account at its definition phase. Unfortunately, the major methods and frameworks supporting measurement programs ---such as Goal Question Metric (GQM), Goal-Driven Software Measurement, GQ(I)M, PSM and ISO/IEC 15939--- do not explicitly address, this issue, which is especially important in small and medium settings, where low measurement maturity level is typical and there are more measurement implementation constraints. Additionally, these companies usually have poor measurement knowledge, limited resources and budget, which prevent measurement integration in the corporate culture. This restricts measurement support in these companies and increases the chances of failure. In this paper we will be looking at an adaptation of the software measurement maturity method developed by Daskalantonakis. The so-called "MIS-PyME maturity model" is focused on giving support towards measurement program definition and is integrated in MIS-PyME, a methodological framework for measurement suited to small and medium settings.
Extending cable theory to heterogeneous dendrites
Authors: Claude Meunier, Boris Lamotte d'Incamps
Venue: Neural Computation (2008)

Dendrites may exhibit many types of electrical and morphological heterogeneities at the scale of a few micrometers. Models of neurons, even so-called detailed models, rarely consider such heterogeneities. Small-scale fluctuations in the membrane conductances and the diameter of dendrites are generally disregarded and spines merely incorporated into the dendritic shaft. Using the two-scales method known as homogenization, we establish explicit expressions for the small-scale fluctuations of the membrane voltage, and we derive the cable equation satisfied by the voltage when these fluctuations are averaged out. This allows us to rigorously establish under what conditions a heterogeneous dendrite can be approximated by a homogeneous cable. We consider different distributions of synapses, orderly or random, on a passive dendrite, and we investigate when replacing excitatory and inhibitory synaptic conductances by their local averages leads to a small error in the voltage. This indicates in which regimes the approximations made in compartmental models are justified. We extend these results to active membranes endowed with voltage-dependent conductances or NMDA receptors. Then we examine under which conditions a spiny dendrite behaves as a smooth dendrite. We discover a new regime where this holds true, namely, when the conductance of the spine neck is small compared to the conductance of the synapses impinging on the spine head. Spines can then be taken into account by an effective excitatory current, the capacitance of the dendrite remaining unchanged. In this regime, the synaptic current transmitted from a spine to the dendritic shaft is strongly attenuated by the weak coupling conductance, but the total current they deliver can be quite substantial. These results suggest that pedunculated spines and stubby spines might play complementary roles in synaptic integration. Finally, we analyze how varicosities affect voltage diffusion in dendrites and discuss their impact on the spatiotemporal integration of synaptic input.
Bouncer: securing software by blocking bad input
Authors: Manuel Costa
Venue: Proceedings of the 2nd workshop on Recent advances on intrusiton-tolerant systems (2008)

Attackers exploit software vulnerabilities to control or crash programs. Bouncer uses existing software instrumentation techniques to detect attacks and it generates filters automatically to block exploits of the target vulnerabilities. The filters are deployed automatically by instrumenting system calls to drop exploit messages. These filters introduce low overhead and they allow programs to keep running correctly under attack. Previous work computes filters using symbolic execution along the path taken by a sample exploit, but attackers can bypass these filters by generating exploits that follow a different execution path. Bouncer introduces three techniques to generalize filters so that they are harder to bypass: a new form of program slicing that uses a combination of static and dynamic analysis to remove unnecessary conditions from the filter; symbolic summaries for common library functions that characterize their behavior succinctly as a set of conditions on the input; and generation of alternative exploits guided by symbolic execution. Bouncer filters have low overhead, they do not have false positives by design, and our results show that Bouncer can generate filters that block all exploits of some real-world vulnerabilities.
Kernel Maximum a Posteriori Classification with Error Bound Analysis
Authors: Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Kernel methods have been widely used in data classification. Many kernel-based classifiers like Kernel Support Vector Machines (KSVM) assume that data can be separated by a hyperplane in the feature space. These methods do not consider the data distribution. This paper proposes a novel Kernel Maximum A Posteriori (KMAP) classification method, which implements a Gaussian density distribution assumption in the feature space and can be regarded as a more generalized classification method than other kernel-based classifier such as Kernel Fisher Discriminant Analysis (KFDA). We also adopt robust methods for parameter estimation. In addition, the error bound analysis for KMAP indicates the effectiveness of the Gaussian density assumption in the feature space. Furthermore, KMAP achieves very promising results on eight UCI benchmark data sets against the competitive methods.
TS-Animation: A Track-Based Sketching Animation System
Authors: Guangyu Wu, Danli Wang, Guozhong Dai
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

Computer has been widely used in classroom. Yet most of them can only provide static slides in the project mode, which are not attractive to children, especially to the younger ones. On contrast animations are not only attractive but also expressive. Using some animations in classroom makes the children more active and enhances their learning efficiency. However, most of current animation tools are either too complicated to common users, or specific domain based. Aimed at removing the complexity barrier and allowing nonprofessional users to create a wide variety of animations quickly, we propose a sketching animation system. A kind of track-based method is adopted to make creating animations as easy as drawing. Motion coordination is simplified by providing the tool of motion time warping. The interface of our system allows most of the important motions to be set by pen gestures.
Integration of Game Elements with Role Play in Collaborative Learning -- A Case Study of Quasi-GBL in Chinese Higher Education
Authors: Zhi Han, Zhenhong Zhang
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

The reason that most undergraduate students in China spend a lot more time playing computer games rather than learning is not that learning is too hard, but it is boring, while playing games is fun. How to provide appropriate and interesting opportunities that can engage students and improve the learning process? This paper discusses an innovatory education paradigm quasi-GBL, which integrates game elements with role play in collaborative learning. Case study of quasi-GBL in an undergraduate course "Software Engineering" reveals that quasi-GBL is successful in achieving experiential and fun learning, offering a variety of knowledge presentations, and creating opportunities for knowledge application.
Normalization of Temporal Information in Estonian
Authors: Margus Treumuth
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

I present a model for processing temporal information in Estonian natural language. I have built a tool to convert natural-language calendar expressions to semi-formalized semantic representation. I have further used this representation to construct formal SQL constraints, which can be enforced on any relational database. The model supports compound expressions (conjunctive and disjunctive), negation and exception expressions. The system is built to work on Oracle databases and is currently running on Oracle 10g with a PHP web interface.
Brief paper: A degree of flexibility in Lyapunov inequalities for establishing input-to-state stability of interconnected systems
Authors: Hiroshi Ito
Venue: Automatica (Journal of IFAC) (2008)

In this paper, a novel approach to constructing flexible Lyapunov inequalities is developed for establishing Input-to-State Stability (ISS) of interconnection of nonlinear time-varying systems. It aims at a useful tool for using nonlinear small-gain conditions by allowing some flexibility in Lyapunov inequalities each subsystem is to satisfy. In the application of the ISS small-gain ''theorem'', achieving a Lyapunov inequality conforming to a nonlinear small-gain ''condition'' is not a straightforward task. The proposed technique provides us with many Lyapunov inequalities with which a single trade-off condition between subsystems gains can establish the ISS property of the interconnected system. Proofs are based on explicit construction of Lyapunov functions.
Reward Maximization for Embedded Systems with Renewable Energies
Authors: Clemens Moser, Jian-Jia Chen, Lothar Thiele
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

Renewable energies can enable embedded systems to be functional indefinitely. In particular for small autonomous sensors, energy harvesting techniques have attracted much interest. This paper considers systems which provide services periodically with adjustable quality evaluated in terms of rewards. The reward garnered for one service is monotonically increasing and strictly concave with respect to the energy consumption of the service. There exist two major constraints which arise due to the burstiness of common energy sources: (1) The harvested energy is temporarily low and the service must be lowered or suspended. (2) During bursts, the harvested energy exceeds the battery capacity. To resolve these issues, we propose algorithms to derive optimal solutions which maximize the overall reward. Furthermore, we determine the minimum battery capacity necessary to optimally exploit a given power source. By applying real data recorded for photovoltaic cells as the harvested energy, simulations illuminate the merits of our algorithms.
A Comprehensive Segmentation, Registration, and Cancer Detection Scheme on 3 Tesla In Vivo Prostate DCE-MRI
Authors: Satish Viswanath, B. Nicolas Bloch, Elisabeth Genega, Neil Rofsky, Robert Lenkinski, Jonathan Chappelow, Robert Toth, Anant Madabhushi
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Recently, high resolution 3 Tesla (T) Dynamic Contrast-Enhanced MRI (DCE-MRI) of the prostate has emerged as a promising modality for detecting prostate cancer (CaP). Computer-aided diagnosis (CAD) schemes for DCE-MRI data have thus far been primarily developed for breast cancer and typically involve model fitting of dynamic intensity changes as a function of contrast agent uptake by the lesion. Comparatively there is relatively little work in developing CAD schemes for prostate DCE-MRI. In this paper, we present a novel unsupervised detection scheme for CaP from 3 T DCE-MRI which comprises 3 distinct steps. First, a multi-attribute active shape model is used to automatically segment the prostate boundary from 3 T in vivo MR imagery. A robust multimodal registration scheme is then used to non-linearly align corresponding whole mount histological and DCE-MRI sections from prostatectomy specimens to determine the spatial extent of CaP. Non-linear dimensionality reduction schemes such as locally linear embedding (LLE) have been previously shown to be useful in projecting such high dimensional biomedical data into a lower dimensional subspace while preserving the non-linear geometry of the data manifold. DCE-MRI data is embedded via LLE and then classified via unsupervised consensus clustering to identify distinct classes. Quantitative evaluation on 21 histology-MRI slice pairs against registered CaP ground truth estimates yielded a maximum CaP detection accuracy of 77.20% while the popular three time point (3TP) scheme yielded an accuracy of 67.37%.
Analyses the Modification Functions of the Drought Monitoring Model Based on the Cloud Parameters Method
Authors: Liangming Liu, Daxiang Xiang, Zheng Zhou, Xinyi Dong
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

This paper mainly introduces the drought monitoring model based on the cloud parameters method and Remote Sensing data with a stable performance to the temporal and spatial variation of remote sensing data, especially in the spatial scale. Based on the fundamental of solar radiation, we deduce the spatial modification functions about the different drought levels with the regression method. Meanwhile, we validate the stability and adaptability of the temporal and spatial modification function through four different models: the original model, with the only temporal modified model, with the only spatial modified model and with both temporal and spatial modified model. Finally, we concluded the modified drought monitoring model's stability and adaptability in the temporal and spatial scales.
ICT strategies of democratic intermediaries: A view on the political system in the digital age
Authors: Arthur Edwards
Venue: Information Polity (2006)

A conceptual framework is proposed for discussing the ICT strategies of intermediaries and their effects on democratic intermediation. The main line of reasoning is that both 'disintermediation' and 're-intermediation' have to be related to specific models of democracy and styles of citizenship. The linkage strategies of preference intermediaries, the supportive strategies of information intermediaries and the facilitative strategies of interaction intermediaries are discussed. The quality of democracy would be dependent on the interplay between different democratic practices, types of citizenship and intermediaries.
Web Based Telematics Application for Robotics
Authors: Dorin Popescu, Dan Selisteanu, Ionut Dinulescu, Livia Carmen Popescu
Venue: Proceedings of the 2008 The Third International Multi-Conference on Computing in the Global Information Technology (iccgi 2008) (2008)

The paper presents the work for development of a telematics application for robotics field. First, it was developed a client-server application and then a web based application. A range of remote experiments with a mobile robot with particular emphasis on motor control, obstacle avoidance, image processing and their application to trajectory control can be done by the users. The users learn the microcontroller programming, sensor use, path planning, trajectory following. The idea is for the users to be able to perform real experiments, in real time, on real equipment, but over the Internet. The remote user is connected by Internet to a dedicated computer used for controlling and monitoring the mobile robot.