ppxscal/embedding_network huggingface dataset:
Adding XMP support to firefox
Authors: Péter Jeszenszky
Venue: Acta Cybernetica (2007)

XMP (Extensible Metadata Platform) is an RDF-based framework of Adobe Systems Incorporated that supports the embedding of metadata in application files. If it becomes widely used on the web, it will provide a rich source of metadata to semantic web applications, too. This paper presents a solution to add a unique feature to the popular Firefox web browser, the capability to extract XMP metadata from web resources. The solution is based on the Piggy Bank Firefox extension that turns Firefox into a "semantic web browser".
Communication-space tradeoffs for unrestricted protocols
Authors: P. Beame, M. Tompa
Venue: Proceedings of the 31st Annual Symposium on Foundations of Computer Science (1990)

Communicating branching programs are introduced, and a general technique for demonstrating communication-space tradeoffs for pairs of communicating branching programs is developed. The technique is used to prove communication-space tradeoffs for any pair of communicating branching programs that hashes according to a universal family of hash functions. Other tradeoffs follow from this result. For example any pair of communicating Boolean branching programs that computes matrix-vector products over GF(2) requires communication-space product Omega (n/sup 2/). These are the first examples of communication-space tradeoffs on a completely general model of communicating processes.
Bayesian nonstationary source separation
Authors: Qinghua Huang, Jie Yang, Yue Zhou
Venue: Neurocomputing (2008)

A Bayesian nonstationary source separation algorithm is proposed in this paper to recover nonstationary sources from noisy mixtures. In order to exploit the temporal structure of the data, we use a time-varying autoregressive (TVAR) process to model each source signal. Then variational Bayesian (VB) learning is adopted to integrate the source model with blind source separation (BSS) in probabilistic form. Our separation algorithm makes full use of temporally correlated prior information and avoids overfitting in separation process. Experimental results demonstrate that our vbICA-TVAR algorithm learns the temporal structure of sources and acquires cleaner source reconstruction.
A systematic approach for the design of ladder based switched current bandpass filter
Authors: Maneesha Gupta, Pragya Varshney, G. S. Visweswaran
Venue: Proceedings of the 5th WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing (2006)

A systematic approach for the design of Switched Current (SI) ladder filters is described. The specifications of the filter in z-domain are used to obtain continued fraction expansions (CFE). Signal Flow Graphs (SFG) of each row of the expansion is derived and then these SFG are directly transformed into switched current structures (integrators and amplifiers). The SI blocks thus obtained are connected in ladder form to generate the required SI filter circuit. This approach can be used for all filter types. A second order bandpass filter is used to demonstrate the utility of the approach.
On the effectiveness of phase based regression models to trade power and performance using dynamic processor adaptation
Authors: Subhasis Banerjee, G. Surendra, S. K. Nandy
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

Microarchitecture optimizations, in general, exploit the gross program behavior for performance improvement. Programs may be viewed as consisting of different ''phases'' which are characterized by variation in a number of processor performance metrics. Previous studies have shown that many of the performance metrics remain nearly constant within a ''phase''. Thus, the change in program ''phases'' may be identified by observing the change in the values of these metrics. This paper aims to exploit the time varying behavior of programs for processor adaptation. Since the resource usage is not uniform across all program ''phases'', the processor operates at varying levels of underutilization. During phases of low available Instruction Level Parallelism (ILP), resources may not be fully utilized while in other phases, more resources may be required to exploit all the available ILP. Thus, dynamically scaling the resources based on program behavior is an attractive mechanism for power-performance trade-off. In this paper we develop per-phase regression models to exploit the phase behavior of programs and adequately allocate resources for a target power-performance trade-off. Modeling processor performance-power using such a regression model is an efficient method to evaluate an architectural optimization quickly and accurately. We also show that the per-phase regression model is better suited than an ''unified'' regression model that does not use phase information. Further, we describe a methodology to allocate processor resources dynamically by using regression models which are developed at runtime. Our simulation results indicate that average energy savings of 20% can be achieved with respect to a maximally configured system with negligible impact on performance for most of the SPEC-CPU and MEDIA benchmarks.
Simulation of Buffer Management Policies in Networks for Grids
Authors: Agustín Caminero, Anthony Sulistio, Blanca Caminero, Carmen Carrión, Rajkumar Buyya
Venue: Proceedings of the 41st Annual Simulation Symposium (anss-41 2008) (2008)

Grid technologies are emerging as the next generation of distributed computing, allowing the aggregation of resources that are geographically distributed across different locations. The network remains an important requirement for any Grid application, as entities involved in a Grid system (such as users, services, and data) need to communicate with each other over a network. The performance of the network must therefore be considered when carrying out tasks such as scheduling, migration or monitoring of jobs. Network buffers management policies affect the network performance, as they can lead to poor latencies (if buffers become too large), but also leading to a lot of packet droppings and low utilization of links, when trying to keep a low buffer size. Therefore, network buffers management policies should be considered when simulating a real Grid system. In this paper, we introduce network buffers management policies into the Grid Sim simulation toolkit.Our framework allows new policies to be implemented easily, thus enabling researchers to create more realistic network models. Fields which will harness our work are scheduling, or QoS provision. We present a comprehensive description of the overall design and a use case scenario demonstrating the conditions of links varied over time.
Online kernel selection for Bayesian reinforcement learning
Authors: Joseph Reisinger, Peter Stone, Risto Miikkulainen
Venue: Proceedings of the 25th international conference on Machine learning (2008)

Kernel-based Bayesian methods for Reinforcement Learning (RL) such as Gaussian Process Temporal Difference (GPTD) are particularly promising because they rigorously treat uncertainty in the value function and make it easy to specify prior knowledge. However, the choice of prior distribution significantly affects the empirical performance of the learning agent, and little work has been done extending existing methods for prior model selection to the online setting. This paper develops Replacing-Kernel RL, an online model selection method for GPTD using sequential Monte-Carlo methods. Replacing-Kernel RL is compared to standard GPTD and tile-coding on several RL domains, and is shown to yield significantly better asymptotic performance for many different kernel families. Furthermore, the resulting kernels capture an intuitively useful notion of prior state covariance that may nevertheless be difficult to capture manually.
Enhanced qualitative probabilistic networks for resolving trade-offs
Authors: Silja Renooij, Linda C. van der Gaag
Venue: Artificial Intelligence (2008)

Qualitative probabilistic networks were designed to overcome, to at least some extent, the quantification problem known to probabilistic networks. Qualitative networks abstract from the numerical probabilities of their quantitative counterparts by using signs to summarise the probabilistic influences between their variables. One of the major drawbacks of these qualitative abstractions, however, is the coarse level of representation detail that does not provide for indicating strengths of influences. As a result, the trade-offs modelled in a network remain unresolved upon inference. We present an enhanced formalism of qualitative probabilistic networks to provide for a finer level of representation detail. An enhanced qualitative probabilistic network differs from a basic qualitative network in that it distinguishes between strong and weak influences. Now, if a strong influence is combined, upon inference, with a conflicting weak influence, the sign of the net influence may be readily determined. Enhanced qualitative networks are purely qualitative in nature, as basic qualitative networks are, yet allow for resolving some trade-offs upon inference.
A Reliable Chunkless Peer-to-Peer Architecture for Multimedia Streaming
Authors: R. Bernardini, R. Rinaldo, A. Vitali
Venue: Proceedings of the Data Compression Conference (2008)

In this paper we propose a chunkless structure for multimedia distribution over peer-to-peer networks. With the proposed approach, the original multimedia packets are partitioned into several reduced packets whose transmission requires a fraction 1/R of the bandwidth required by the original data. The generation of the reduced packets depends on a random seed that can be randomly chosen by each node. The reconstruction of the original packet is possible as soon as R reduced packets are received from the other peers. The proposed scheme has a very small computational complexity, it is transparent to cryptography and it is independent on the used multimedia signal coding scheme. Analytical expressions of the start-up time and the probability of information recovery are obtained.
Constraint based role based access control in the SECTET-framework: A model-driven approach
Authors: Muhammad Alam Michael Hafner Ruth Breu
Venue: Journal of Computer Security (2008)

With respect to Service Oriented Architectures (SOA's) paradigm, the core Role Based Access Control (RBAC) has several limitations. In SOA, permissions to execute web services are not assigned statically to roles but are associated with a set of Permission Assignment Constraints (PAC) upon the fulfilment of which a role is assigned a permission to execute a web service. Further, the RBAC does not support partial inheritance which is an integral requirement in SOA. A major challenge in SOA is the inheritance of permissions associated with PAC in the presence of role hierarchies. This contribution has three objectives. First we propose an extension to Role Based Access Control (available at csrc.nist.gov/rbac/), which we call Constraint based RBAC (CRBAC), in order to make RBAC applicable to the dynamic environment of SOA. Within CRBAC, a high-level language - called SECTET-PL (available at http:// qe-informatik.uibk.ac.at/~muhammad/TechnicalReportSECTETPL.pdf) is used for the specification of PAC. Being part of the SECTET-framework for model-driven security for B2B-workflows, SECTET-PL is a policy language influenced by OCL (available at http://www.omg.org/docs/ptc/03-10-14.pdf) and interpreted in the context of UML models. Using the Model Driven Architecture (MDA) (available at http://www.omg.org/mda) paradigm, we then describe the transformation of high-level security models to low-level web services standard artefacts with the help of the Eclipse Modelling Framework and OpenArchitectureWare. Finally, we present the target architecture of the SECTET-framework used to realize the security artefacts generated from the transformations and thus completes the cycle of MDA.
An evaluation of void-filling interpolation methods for SRTM data
Authors: H. I. Reuter, A. Nelson, A. Jarvis
Venue: International Journal of Geographical Information Science (2007)

The Digital Elevation Model that has been derived from the February 2000 Shuttle Radar Topography Mission (SRTM) has been one of the most important publicly available new spatial data sets in recent years. However, the 'finished' grade version of the data (also referred to as Version 2) still contains data voids (some 836,000 km2)-and other anomalies-that prevent immediate use in many applications. These voids can be filled using a range of interpolation algorithms in conjunction with other sources of elevation data, but there is little guidance on the most appropriate void-filling method. This paper describes: (i) a method to fill voids using a variety of interpolators, (ii) a method to determine the most appropriate void-filling algorithms using a classification of the voids based on their size and a typology of their surrounding terrain; and (iii) the classification of the most appropriate algorithm for each of the 3,339,913 voids in the SRTM data. Based on a sample of 1304 artificial but realistic voids across six terrain types and eight void size classes, we found that the choice of void-filling algorithm is dependent on both the size and terrain type of the void. Contrary to some previous findings, the best methods can be generalised as: kriging or inverse distance weighting interpolation for small and medium size voids in relatively flat low-lying areas; spline interpolation for small and medium-sized voids in high-altitude and dissected terrain; triangular irregular network or inverse distance weighting interpolation for large voids in very flat areas, and an advanced spline method (ANUDEM) for large voids in other terrains.
An architecture for the provision of content networks based on IMS, metadata, presence and P2P technologies
Authors: Eduardo Ribeiro, Rui J. Lopes
Venue: Proceedings of the 2007 Workshop on Middleware for next-generation converged networks and applications (2007)

The Internet is currently being designed and used in a way that is strongly influenced by inter-personal communications and content-based services. Content Networks, having presence and audiovisual metadata descriptions as central concepts, can play an important role in the provision of these services. Existing standards from the ISO/IEC MPEG (MPEG-7,-21) and IETF (PIDF, RPID) provide the technologies for these elementary features. This paper contributes to the deployment of Content Networks by proposing a layered architecture where the IMS Multimedia Subsystem and P2P-based midlleware tackle the problem of terminal, networks heterogeneity and the integration of different presence and metadata tools. The P2P-based middleware is used to construct autonomously self-organized, context and interest based communities by providing overlay infrastructures for the interconnection of different Content Networks components. The results obtained from implementing this architecture using Open IMS Core and Scribe open platforms show that the proposed architecture can be used for the creation and deployment of services on Content Networks.
Momentum-Based Motion Detection Methodology for Handoff in Wireless Networks
Authors: Tein-Yaw Chung, Chih-Hung Hsu, Yung-Mu Chen, K. Robert Lai
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (2008)

This paper presents a novel motion detection scheme by using the Momentum of Received Signal Strength (MRSS) to improve the quality of handoff in a general wireless network. MRSS can detect the motion state of a mobile node (MN) without assistance of any positioning service. Although MRSS is sensitive in detecting user's motion, it is static and fails to detect quickly the motion changes of users. Thus, a novel motion state dependent MRSS scheme called Dynamic MRSS (DMRSS) algorithm is proposed to address this issue. Extensive simulation experiments were conducted to study performance of our presented algorithms.The simulation results show that MRSS and DMRSS can be used to assist a handoff algorithm in substantially reducing unnecessary handoff and saving power.
Asymmetric Multi-level Diversity Coding
Authors: Soheil Mohajer, Chao Tian, Suhas N. Diggavi
Venue: Proceedings of the Data Compression Conference (2008)

Symmetric multilevel diversity coding was introduced by Roche et al, where a set of K information sources is encoded by K encoders and the decoders reconstruct sources 1,...,k, where k is the number of encoders to which they have access. In this paper, we formulate an asymmetric multilevel diversity coding problem, where a set of 2^K-1 information sources is encoded by K encoders into K streams/descriptions. There are 2^K-1 decoders, each of which has access to a non-empty subset of the encoded messages. The decoders are assigned with ordered levels, and each of them has to decode a subset of the information sources, according to its level, which depends on the set of encoders to which it has access, not just the cardinality. We obtain a single letter characterization of the complete achievable rate region for the 3-description problem. In doing so, we show that it is necessary to jointly encode independent sources (i.e., similar to network coding), and that linear codes are optimal for this problem.
A Computer Aided Diagnosis System in Mammography Using Artificial Neural Networks
Authors: Guodong Zhang, Peiyu Yan, Hong Zhao, Xin Zhang
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

In this paper we present a method for developing a fully automated computer aided diagnosis (CAD) system to help radiologist in detecting and diagnosing micro-calcifications (MCCs) in digital format mammograms. One aim of the CAD system is to increase the effectiveness and efficiency of screening procedures by using computer. Another aim of the CAD is to extract and analyze the characteristics of vary lesions in an objective manner, then can improve the diagnostic accuracy and reduce the numbers of false-positive diagnoses of malignancies. Automatic segmentation, features extraction, suspicious area detection, classification and a back propagation neural network (BPNN) techniques were used in the development of this system. And the BPNN was used to classifying the marked regions into benign and malignant as the most important stage.
Bayesian Inference and Optimal Design for the Sparse Linear Model
Authors: Matthias W. Seeger
Venue: The Journal of Machine Learning Research (2008)

The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maximum a posteriori sparse solutions and neglect to represent posterior uncertainties. In this paper, we address problems of Bayesian optimal design (or experiment planning), for which accurate estimates of uncertainty are essential. To this end, we employ expectation propagation approximate inference for the linear model with Laplace prior, giving new insight into numerical stability properties and proposing a robust algorithm. We also show how to estimate model hyperparameters by empirical Bayesian maximisation of the marginal likelihood, and propose ideas in order to scale up the method to very large underdetermined problems. We demonstrate the versatility of our framework on the application of gene regulatory network identification from micro-array expression data, where both the Laplace prior and the active experimental design approach are shown to result in significant improvements. We also address the problem of sparse coding of natural images, and show how our framework can be used for compressive sensing tasks. Part of this work appeared in Seeger et al. (2007b). The gene network identification application appears in Steinke et al. (2007).
An efficient incremental algorithm for min-area retiming
Authors: Jia Wang, Hai Zhou
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

As one of the most effective sequential optimization techniques, retiming is a structural transformation that relocates flip-flops in a circuit without changing its functionality. The min-area retiming problem seeks a solution with the minimum flip-flop area (or number) under a given clock period. Even though having polynomial runtime, the best existing algorithms for this problem still need to first construct a dense path graph and then find a min-cost network flow on it, thus incur huge storage and time expenses for large circuits. Recently, provable incremental algorithms have been discovered for min-period retiming, and heuristic incremental algorithms have been proposed for min-area retiming. However, given the complexity of the problem, min-area retiming is still resisting an efficient provable incremental algorithm. In this paper, we fill the gap by presenting an efficient algorithm to solve the min-area retiming problem incrementally and optimally. Contrary to existing approaches, no dense path graph is constructed; only the active timing constraints are dynamically generated in the algorithm. Experimental results show that the total runtime of our algorithm for all the benchmarks is at least 60 x faster than the best existing approach.
Quantitative Retrieval of Geophysical Parameters Using Satellite Data
Authors: Yong Xue, Wei Wan, Yingjie Li, Jie Guang, Linyian Bai, Ying Wang, Jianwen Ai
Venue: Computer (2008)

The remote sensing information service grid node (RSIN) is a tool for dealing with climate change and quantitative environmental monitoring. Based on the high-throughput computing grid, RSIN enables a workflow management system for data placement. The accompanying unified data-and-computation-schedule algorithm helps load balancing between and within workflow steps.
CVD oriented growth of carbon nanotubes using AlPO4-5 and L type zeolites
Authors: I. Martin, G. Rius, P. Atienzar, L. Teruel, N. Mestres, F. Perez-Murano, H. Garcia, P. Godignon, A. Corma, E. Lora-Tamayo
Venue: Microelectronic Engineering (2008)

Control over single wall carbon nanotube structure, positioning and orientation is one of the main challenges for the development of carbon nanotube based electronics. A novel approach consists in placing carbon nanotubes catalyst inside the pores of a zeolite so that control over the nanotube diameter and its growth direction can be achieved. We present the relation between CVD process and carbon nanotube growth when placing the catalyst inside the pores of AlPO"4-5 and L type zeolites. By SEM and Raman characterization, we have determined the influence of vacuum pre-treatment and catalyst activation steps. This is the first step towards obtaining batch synthesis of oriented nanotubes at wafer scale.
More natural end-user software engineering
Authors: Brad A. Myers, Andrew J. Ko, Sun Young Park, Jeffrey Stylos, Thomas D. LaToza, Jack Beaton
Venue: Proceedings of the 4th international workshop on End-user software engineering (2008)

The "Natural Programming" project at Carnegie Mellon University has been working for more than 10 years to make programming more "natural", or closer to the way people think. We have addressed the needs of all kinds of programmers: novices, professionals and end-user programmers. Many studies were performed which provided new insights and led to new models of programmers. From these insights and models, we created new programming languages and environments. Evaluations of the resulting systems have shown that they are effective and successful. This paper provides an overview of the entire 10-year Natural Programming project, but focuses on our new results since WEUSE-III in Dagstuhl.