ppxscal/embedding_network huggingface dataset:
Discontinuous Galerkin Methods Based on Weighted Interior Penalties for Second Order PDEs with Non-smooth Coefficients
Authors: Paolo Zunino
Venue: Journal of Scientific Computing (2009)

We develop and analyze a Discontinuous Galerkin (DG) method based on weighted interior penalties (WIP) applied to second order (elliptic) PDEs and in particular to advection-diffusion-reaction equations featuring non-smooth and possibly vanishing diffusivity. First of all, looking at the derivation of a DG scheme with a bias to domain decomposition methods, we carefully discuss the set up of the discretization scheme in a general framework putting into evidence the helpful role of the weights and the connection with the well known Local Discontinuous Galerkin schemes (LDG). Then, we address the a-priori error analysis of the method, recovering optimal error estimates in suitable norms. By virtue of the introduction of the weighted penalties, these results turn out to be robust with respect to the diffusion parameter. Furthermore, we discuss the derivation of an a-posteriori local error indicator suitable for advection-diffusion-reaction problems with highly variable, locally small diffusivity. All the theoretical results are illustrated and discussed by means of numerical experiments.
Measuring the impact of third place attachment on the adoption of a place-based community technology
Authors: Shelly D. Farnham, Joseph F. McCarthy, Yagnesh Patel, Sameer Ahuja, Daniel Norman, William R. Hazlewood, Josh Lind
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

CoCollage is a placed-based community technology that leverages the power of online social networking to facilitate awareness and face-to-face interactions in a third place. We adapted standardized measures of place attachment, social networks and psychological sense of community to provide a framework grounded in the social science literature for studying real world adoption of place-based community technologies. We found the standardized measures of place attachment and psychological sense of community meaningfully predicted likelihood of technology adoption and usage in a café. We discuss some lessons learned from our initial deployment of CoCollage in a real-world setting to support a nascent place-based community.
A framework for estimating NBTI degradation of microarchitectural components
Authors: Michael DeBole, K. Ramakrishnan, Varsha Balakrishnan, Wenping Wang, Hong Luo, Yu Wang, Yuan Xie, Yu Cao, N. Vijaykrishnan
Venue: Proceedings of the 2009 Asia and South Pacific Design Automation Conference (2009)

Degradation of device parameters over the lifetime of a system is emerging as a significant threat to system reliability. Among the aging mechanisms, wearout resulting from NBTI is of particular concern in deep submicron technology generations. To facilitate architectural level aging analysis, a tool capable of evaluating NBTI vulnerabilities early in the design cycle has been developed. The tool includes workload-based temperature and performance degradation analysis across a variety of technologies and operating conditions, revealing a complex interplay between factors influencing NBTI timing degradation.
Do software libraries evolve differently than applications?: an empirical investigation
Authors: Stéphane Vaucher, Houari Sahraoui
Venue: Proceedings of the 2007 Symposium on Library-Centric Software Design (2007)

More and more, developers use reusable components like libraries to produce high quality software systems. These systems need to satisfy not only the initial demands of their stakeholders, but they need to also offer support for future, changing requirements. While several studies have looked at the cost of modifying systems, there exists no work verifying if libraries evolve differently than applications. This study attempts to do so quantitatively. In this paper, we define design changes metrics to estimate the amount of high-level change required of individual classes and use metrics to describe their structure. These measures are then used as inputs in models capable of predicting code change. We used machine learning techniques to build these models and tested them on the evolution of industrial open-source systems. Two of the systems were libraries, and two were standalone applications. We found that while design changes are systematically correlated with code changes, structure metrics are better predictors of code change in libraries with well developed class hierarchies. With the two applications without this characteristic, structure alone was a poor predictor.
A learning classifier system for mazes with aliasing clones
Authors: Zhanna V. Zatuchna, Anthony J. Bagnall
Venue: Natural Computing: an international journal (2009)

Maze problems represent a simplified virtual model of the real environment and can be used for developing core algorithms of many real-world application related to the problem of navigation. Learning Classifier Systems (LCS) are the most widely used class of algorithms for reinforcement learning in mazes. However, LCSs best achievements in maze problems are still mostly bounded to non-aliasing environments, while LCS complexity seems to obstruct a proper analysis of the reasons for failure. Moreover, there is a lack of knowledge of what makes a maze problem hard to solve by a learning agent. To overcome this restriction we try to improve our understanding of the nature and structure of maze environments. In this paper we describe a new LCS agent that has a simpler and more transparent performance mechanism. We use the structure of a predictive LCS model, strip out the evolutionary mechanism, simplify the reinforcement learning procedure and equip the agent with the ability to Associative Perception, adopted from psychology. We then assess the new LCS with Associative Perception on an extensive set of mazes and analyse the results to discover which features of the environments play the most significant role in the learning process. We identify a particularly hard feature for learning in mazes, aliasing clones, which arise when groups of aliasing cells occur in similar patterns in different parts of the maze. We discuss the impact of aliasing clones and other types of aliasing on learning algorithms.
An incentive compatible reputation mechanism for ubiquitous computing environments
Authors: Jinshan Liu, Valérie Issarny
Venue: Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services (2006)

The vision of ubiquitous computing is becoming a reality thanks to the advent of portable devices and the advances in wireless networking technologies. It aims to facilitate user tasks through seamless utilization of services available in the surrounding environments. In such distributed environments featuring openness, interactions, especially service provision and consumption, between entities that are unknown or barely known to each other, are commonplace. Trust management through reputation mechanism to facilitate such interactions is recognized as an important element of ubiquitous computing. It is, however, faced by the problems of how to stimulate reputation information sharing and honest recommendation elicitation. We present in this paper an incentive compatible reputation mechanism to facilitate the trustworthiness evaluation in ubiquitous computing environments. It is based on probability theory and supports reputation evolution and propagation. Our reputation mechanism not only shows robustness against lies, but also stimulates honest and active recommendations. The latter is realized by ensuring that active and honest recommenders, compared to inactive or dishonest ones, can elicit the most honest (helpful) recommendations and thus suffer the least number of wrong trust decisions, as validated by simulation based evaluation.
High Performance Computing for Eigenvalue Solver in Density-Matrix Renormalization Group Method: Parallelization of the Hamiltonian Matrix-Vector Multiplication
Authors: Susumu Yamada, Masahiko Okumura, Masahiko Machida
Venue: High Performance Computing for Computational Science - VECPAR 2008: 8th International Conference, Toulouse, France, June 24-27, 2008. Revised Selected Papers (2008)

The Density Matrix Renormalization Group (DMRG) method is widely used by computational physicists as a high accuracy tool to obtain the ground state of large quantum lattice models. Since the DMRG method has been originally developed for 1-D models, many extended method to a 2-D model have been proposed. However, some of them have issues in term of their accuracy. It is expected that the accuracy of the DMRG method extended directly to 2-D models is excellent. The direct extension DMRG method demands an enormous memory space. Therefore, we parallelize the matrix-vector multiplication in iterative methods for solving the eigenvalue problem, which is the most time- and memory-consuming operation. We find that the parallel efficiency of the direct extension DMRG method shows a good one as the number of states kept increases.
Promoting Data Mining Methodologies by Architecture-Level Optimizations
Authors: Xin Ge, Enjie Ding, Hongxia Xie
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

This paper presents a new theoretical data mining framework that adapts the existing data mining systems with the architecture of the Knowledge Grid, the mechanism of the ontologies, and the factor of the human-driven knowledge. Aiming at much of the research to date focusing on the technique and algorithms, the new framework describes the essential factors from systemic and technical viewpoints respectively in order to balance the effect between the two aspects.
Utility function of TCP
Authors: Lei Ye, Zhijun Wang, Hao Che, Henry B. C. Chan, Constantino M. Lagoa
Venue: Computer Communications (2009)

Understanding the TCP congestion control mechanism from a global optimization point of view is not only important in its own right, but also crucial to the design of other transport layer traffic control protocols with provable properties. In this paper, we derive a global utility function and the corresponding optimal control law, known as TCP control law, which maximizes the global utility. The TCP control law captures the essential behaviors of TCP, including slow start, congestion avoidance, and the binary nature of congestion feedback in TCP. We find that the utility function of TCP is linear in the slow start phase and is proportional to the additive increase rate and approaches the well-known logarithm function as the data rate becomes large in the congestion avoidance phase. We also find that understanding the slow start phase with a fixed threshold is critical to the design of new transport layer control protocols to enable quality of service features. Finally, as an application, we design a Minimum Rate Guaranteed (MRG) traffic control law that shares the same utility function as the TCP control law. Our simulation study of the MRG control law indicates that it is indeed TCP friendly and can provide minimum rate guarantee as long as the percentage of network resource consumed by the MRG flows is moderately small.
Hybrid Resource Discovery Mechanism in Ad Hoc Grid Using Structured Overlay
Authors: Tariq Abdullah, Luc Onana Alima, Vassiliy Sokolov, David Calomme, Koen Bertels
Venue: Proceedings of the 22nd International Conference on Architecture of Computing Systems (2009)

Resource management has been an area of research in ad hoc grids for many years. Recently, different research projects have focused resource management in centralized, decentralized or in a hybrid manner. In this paper, we discuss a micro economic based, hybrid resource discovery mechanism. The proposed mechanism focuses on the extension of a structured overlay network to manage the (dis)appearance of matchmakers in the grid and to route the messages to the appropriate matchmaker in the ad hoc grid. The mechanism is based on the emergent behavior of the participating nodes and adapts with respect to changes in the ad hoc grid environment. Experiments are executed on PlanetLab to test the scalability and robustness of the proposed mechanism. Simulation results show that our mechanism performs better than previously proposed mechanisms.
Recognition and classification of colon cells applying the ensemble of classifiers
Authors: M. Kruk, S. Osowski, R. Koktysz
Venue: Computers in Biology and Medicine (2009)

The paper presents the application of an ensemble of classifiers for the recognition of colon cells on the basis of the microscope colon image. The solved task include: segmentation of the individual cells from the image using the morphological operations, the preprocessing stages, leading to the extraction of features, selection of the most important features, and the classification stage applying the classifiers arranged in the form of ensemble. The paper presents and discusses the results concerning the recognition of four most important colon cell types: eosinophylic granulocyte, neutrophilic granulocyte, lymphocyte and plasmocyte. The proposed system is able to recognize the cells with the accuracy comparable to the human expert (around 5% of discrepancy of both results).
Non-functional Parameters as First Class Citizens in Service Description and Matchmaking - An Integrated Approach
Authors: Mohamed Hamdy, Birgitta König-Ries, Ulrich Küster
Venue: Service-Oriented Computing - ICSOC 2007 Workshops: ICSOC 2007, International Workshops, Vienna, Austria, September 17, 2007, Revised Selected Papers (2009)

Automatic discovery and invocation of services will only be accepted in practise, if the non-functional, especially QoS, parameters are taken into consideration during matchmaking. In this paper we present how this can be achieved. As an example, we use the DIANE framework and explain how the concepts developed there can be extended to easily accommodate non-functional aspects. Thereby, these aspects become first class citizens given the same importance as functional requirements during service selection.
A Novel Block-DFE Algorithm for DTMB Standard
Authors: Qiuyuan Huang, Yan Xu, Biqi Long
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 01 (2009)

Equalization is a technique often used in wireless communication applications. In this paper a novel block decision feedback equalizer (Block-DFE) algorithm suitable for Chinese Digital Terrestrial Television Multimedia Broadcasting (DTMB) standard is proposed. Our Block-DFE algorithm is based on QR factorization, which is used to solve the least-squares detection problem. We adopt Givens rotations to perform the QR decomposition. The performance of traditional decision feedback equalization (DFE) algorithm, overlap and add Frequency-Domain Equalization (OLA-FDE) algorithm, and Block-DFE algorithm under different SNRs is compared by MATLAB simulation, which proves the advantages of Block-DFE algorithm.
Privacy from promises to protection: privacy guaranteeing execution container
Authors: Michael Maaser, Peter Langendörfer
Venue: Mobile Networks and Applications (2009)

Privacy issues are becoming more and more important especially since the cyber and the real world are converging up to certain extent when using mobile devices. Means that really protect privacy are still missing. The problem is, as soon as a user provides data to a service provider the user looses control over her data. The simple solution is not to provide any data but then many useful services, e.g. navigation applications, cannot be used. In order to solve this problem, we propose privacy guaranteeing execution containers (PGEC). Basically the concept is that the application obtains access to the user data in a specially protected and certified environment, the PGEC. PGECs enable applications to access private user data and guarantee that the user data is deleted as soon as the service is quit. The PGEC also restricts the communication between the application and the service provider to what is explicitly allowed by the service user. In addition to those means the PGEC also implements countermeasures against malicious attacks such as modified host systems and covert channel attacks, which might be misusing CPU load to signal data out of the PGEC. Thus, the PGEC guarantees a "one time use" of the provided private data.
Contingency matrix theory: Statistical dependence in a contingency table
Authors: Shusaku Tsumoto
Venue: Information Sciences: an International Journal (2009)

Chance discovery aims at understanding the meaning of functional dependency from the viewpoint of unexpected relations. One of the most important observations is that such a chance is hidden under a huge number of coocurrencies extracted from a given data. On the other hand, conventional data-mining methods are strongly dependent on frequencies and statistics rather than interestingness or unexpectedness. This paper discusses some limitations of ideas of statistical dependence, especially focusing on the formal characteristics of Simpson's paradox from the viewpoint of linear algebra. Theoretical results show that such a Simpson's paradox can be observed when a given contingency table as a matrix is not regular, in other words, the rank of a contingency matrix is not full. Thus, data-ordered evidence gives some limitations, which should be compensated by human-oriented reasoning.
Caching Content under Digital Rights Management
Authors: Leah Epstein, Amos Fiat, Meital Levy
Venue: Approximation and Online Algorithms: 6th International Workshop, WAOA 2008, Karlsruhe, Germany, September 18-19, 2008. Revised Papers (2009)

Digital rights management systems seek to control the use of proprietary material (e.g., copyrighted movies). The use of DRM introduces a new set of caching issues not previously studied. Technically, these problems include elements of ski rental algorithms as well as paging, and their generalizations, online "capital investment" and generalized caching (the Landlord algorithm). The introduction of DRM restrictions does not impact the competitive ratio by more than a constant factor.
The virtues and vices of equilibrium and the future of financial economics
Authors: J. Doyne Farmer, John Geanakoplos
Venue: Complexity (2009)

The use of equilibrium models in economics springs from the desire for parsimonious models of economic phenomena that take human reasoning into account. This approach has been the cornerstone of modern economic theory. We explain why this is so, extolling the virtues of equilibrium theory; then we present a critique and describe why this approach is inherently limited, and why economics needs to move in new directions if it is to continue to make progress. We stress that this shouldn't be a question of dogma, and should be resolved empirically. There are situations where equilibrium models provide useful predictions and there are situations where they can never provide useful predictions. There are also many situations where the jury is still out, i.e., where so far they fail to provide a good description of the world, but where proper extensions might change this. Our goal is to convince the skeptics that equilibrium models can be useful, but also to make traditional economists more aware of the limitations of equilibrium models. We sketch some alternative approaches and discuss why they should play an important role in future research in economics. &copy; 2008 Wiley Periodicals, Inc. Complexity, 2009
Regulation retrieval using industry specific taxonomies
Authors: Chin Pang Cheng, Gloria T. Lau, Kincho H. Law, Jiayi Pan, Albert Jones
Venue: Artificial Intelligence and Law (2008)

Increasingly, taxonomies are being developed and used by industry practitioners to facilitate information interoperability and retrieval. Within a single industrial domain, there exist many taxonomies that are intended for different applications. Industry specific taxonomies often represent the vocabularies that are commonly used by the practitioners. Their jobs are multi-faceted, which include checking for code and regulatory compliance. As such, it will be very desirable if industry practitioners are able to easily locate and browse regulations of interest. In practice, multiple sources of government regulations exist and they are often organized and classified by the needs of the issuing agencies that enforce them rather than the needs of the communities that use them. One way to bridge these two distinct needs is to develop methods and tools that enable practitioners to browse and retrieve government regulations using their own terms and vocabularies, for example, via existing industry taxonomies. The mapping from a single taxonomy to a single regulation is a trivial keyword matching task. We examine a relatedness analysis approach for mapping a single taxonomy to multiple regulations. We then present an approach for mapping multiple taxonomies to a single regulation by measuring the relatedness of concepts. Cosine similarity, Jaccard coefficient and market basket analysis are used to measure the semantic relatedness between concepts from two different taxonomies. Preliminary evaluations of the three relatedness analysis measures are performed using examples from the civil engineering and building industry. These examples illustrate the potential benefits of regulatory usage from the mapping between various taxonomies and regulations.
CTL and Its Usage in the EDA Industry
Authors: Rohit Kapur, Paul Reuter, Sandeep Bhatia, Brion Keller
Venue: IEEE Design Test (2009)

The Core Test Language, originally developed within the IEEE 1500 development working group but later spun out as an independent standard, specifies the standardized language in which core test information for both wrapped and still-to-be-wrapped cores is described.
A novel parametric fuzzy CMAC network and its applications
Authors: Cheng-Jian Lin, Chi-Yung Lee
Venue: Applied Soft Computing (2009)

This paper shows fundamentals and applications of the novel parametric fuzzy cerebellar model articulation controller (P-FCMAC) network. It resembles a neural structure that derived from the Albus CMAC algorithm and Takagi-Sugeno-Kang parametric fuzzy inference systems. The Gaussian basis function is used to model the hypercube structure and the linear parametric equation of the network input variance is used to model the TSK-type output. A self-constructing learning algorithm, which consists of the self-clustering method (SCM) and the backpropagation algorithm, is proposed. The proposed the SCM scheme is a fast, one-pass algorithm for a dynamic estimation of the number of hypercube cells in an input data space. The clustering technique does not require prior knowledge of things such as the number of clusters present in a data set. The backpropagation algorithm is used to tune the adjustable parameters. Illustrative examples were conducted to show the performance and applicability of the proposed model.