ppxscal/embedding_network huggingface dataset:
A note on recoverability of modular systems
Authors: Philip M. Merlin, David J. Farber
Venue: Proceedings of the May 19-22, 1975, national computer conference and exposition (1975)

In a paper by Gostelow-Van Weert, it was shown that any processes can be described by Petri-nets (PN). Thus PN can be used as a model in the design (or analysis) of any computer system. This approach makes it possible to utilize all the theoretic knowledge developed for PN and thus provides a powerful tool for computer systems (or program) design. In this case, the PN can be used as a framework that provides a tool for: 1. the understanding of the design, 2. handling the incremental changes of the design (without redesigning the entire system), 3. the implementation of desired properties (like recoverability in case of failures, proper termination, mutual exclusion, etc.), and 4. at least, the analysis of the program in order to check if it has the desired properties.
Comparing approximate reasoning and probabilistic reasoning using the Dempster--Shafer framework
Authors: Ronald R. Yager
Venue: International Journal of Approximate Reasoning (2009)

We investigate the problem of inferring information about the value of a variable V from its relationship with another variable U and information about U. We consider two approaches, one using the fuzzy set based theory of approximate reasoning and the other using probabilistic reasoning. Both of these approaches allow the inclusion of imprecise granular type information. The inferred values from each of these methods are then represented using a Dempster-Shafer belief structure. We then compare these values and show an underling unity between these two approaches.
Response surface methodology for simulating hedging and trading strategies
Authors: R. Evren Baysal, Barry L. Nelson, Jeremy Staum
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Suppose that one wishes to evaluate the distribution of profit and loss (P&L) resulting from a dynamic trading strategy. A straightforward method is to simulate thousands of paths (i.e., time series) of relevant financial variables and to track the resulting P&L at every time at which the trading strategy rebalances its portfolio. In many cases, this requires numerical computation of portfolio weights at every rebalancing time on every path, for example, by a nested simulation performed conditional on market conditions at that time on that path. Such a two-level simulation could involve many millions of simulations to compute portfolio weights, and thus be too computationally expensive to attain high accuracy. We show that response surface methodology enables a more efficient simulation procedure: in particular, it is possible to do far fewer simulations by using kriging to model portfolio weights as a function of underlying financial variables.
Predict and relay: an efficient routing in disruption-tolerant networks
Authors: Quan Yuan, Ionut Cardei, Jie Wu
Venue: Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing (2009)

Routing is one of the most challenging open problems in disruption-tolerant networks (DTNs) because of the short-lived wireless connectivity environment. To deal with this issue, researchers have investigated routing based on the prediction of future contacts, taking advantage of nodes' mobility history. However, most of the previous work focused on the prediction of whether two nodes would have a contact, without considering the time of the contact. This paper proposes predict and relay (PER), an efficient routing algorithm for DTNs, where nodes determine the probability distribution of future contact times and choose a proper next hop in order to improve the end-to-end delivery probability. The algorithm is based on two observations: one is that nodes usually move around a set of well-visited landmark points instead of moving randomly; the other is that node mobility behavior is semi-deterministic and could be predicted once there is sufficient mobility history information. Specifically, our approach employs a time-homogeneous semi-markov process model that describes node mobility as transitions between landmarks. Landmark transition and sojourn time probability distributions are determined from nodes' mobility history. A simulation study shows that this approach improves the delivery ratio and also reduces the delivery latency compared to traditional DTN routing schemes.
Structure and Hue Similarity for Color Image Quality Assessment
Authors: Yunyu Shi, Youdong Ding, Ranran Zhang, Jun Li
Venue: Proceedings of the 2009 International Conference on Electronic Computer Technology (2009)

An improved model (SHSIM) for color image quality assessment is proposed in this paper, which is based on the fact that structural and color information are all important for human viewers to evaluate images quality. The relative importance values of two components are determined through the experiments. Our experimental results indicate that SHSIM performs a little better than SSIM which focus on structural information of images, and better than CD-PSNR which works with color information only.
Implementing the Omega failure detector in the crash-recovery failure model
Authors: Cristian Martín, Mikel Larrea, Ernesto Jiménez
Venue: Journal of Computer and System Sciences (2009)

Unreliable failure detectors are mechanisms providing information about process failures, that allow to solve several problems in asynchronous systems, e.g., Consensus. A particular failure detector, Omega, provides an eventual leader election functionality. This paper addresses the implementation of Omega in the crash-recovery failure model. We first propose an algorithm assuming that processes are reachable from the correct process that crashes and recovers a minimum number of times. Then, we propose two algorithms which assume only that processes are reachable from some correct process. Besides this, one of the algorithms requires the membership to be known a priori, while the other two do not.
A Novel Modified Polynomial Network Design for Dialect Recognition
Authors: Hemant A. Patil, T. K. Basu
Venue: Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition (2009)

In this paper, a new method of machine learning,viz., Modified Polynomial Networks (MPN) is proposed for the Dialect Recognition (DR) problem in an Indian language, viz., Marathi. The proposed algorithm for machine learning is interpreted as designing a neural network by viewing it as a curve-fitting (approximation) problem in a high-dimensional space with the help of Radial-Basis Functions (RBF)(polynomials expansion of feature vectors for the present problem). The experiments are shown for open set DR problem (training and testing of the machine done with the different sets of speakers of a particular dialectal zone) in Marathi for Mel Frequency Cepstral Coefficients (MFCC) and Subband Based Cepstral Coefficients (SBCC) (extracted usiing Daubechies wavelets of 8 vanishing moments, i.e., db8) as input cepstral feature vectors to the 2nd order modified polynomial networks.
Evaluating switching neural networks through artificial and real gene expression data
Authors: Marco Muselli, Massimiliano Costacurta, Francesca Ruffino
Venue: Artificial Intelligence in Medicine (2009)

Objective: DNA microarrays offer the possibility of analyzing the expression level for thousands of genes concerning a specific tissue. An important target of this analysis is to derive the subset of genes involved in a biological process of interest. Here, a new promising method for gene selection is proposed, which presents a good level of accuracy and reliability. Methods and materials: The proposed technique adopts switching neural networks (SNN), a particular kind of connectionist models, to assign a relevance value to each gene, thus employing recursive feature addition (RFA) to derive the final list of relevant genes. To fairly evaluate the quality of the new approach, called SNN-RFA, its application on three real and three artificial gene expression datasets, generated according to a proper mathematical model that possesses biological and statistical plausibility, has been considered. In particular, a comparison with other two widely used gene selection methods, namely the signal to noise ratio (S2N) and support vector machines with recursive feature elimination (SVM-RFE), has been performed. Results: In all the considered cases SNN-RFA achieves the best performances, arriving to determine the whole collection of relevant genes in one of the three artificial datasets. The S2N method exhibits a quality similar to that of SNN-RFA, whereas SVM-RFE shows the worst behavior. Conclusion: The quality of the proposed method SNN-RFA has been established together with the usefulness of the mathematical model adopted to generate the artificial datasets of gene expression levels.
A theoretical approach to the use of cyberinfrastructure in geographical analysis
Authors: Shaowen Wang, Marc P. Armstrong
Venue: International Journal of Geographical Information Science (2009)

This paper presents a theoretical approach that has been developed to capture the computational intensity and computing resource requirements of geographical data and analysis methods. These requirements are then transformed into a common framework, a grid-based representation of a spatial computational domain, which supports the efficient use of emerging cyberinfrastructure environments. Two key types of transformational functions (data-centric and operation-centric) are identified and their relationships are explained. The application of the approach is illustrated using two geographical analysis methods: inverse distance weighted interpolation and the spatial statistic. We describe the underpinnings of these two methods, present their conventional sequential algorithms, and then address their latent parallelism based on a spatial computational domain representation. Through the application of this theoretical approach, the development of domain decomposition methods is decoupled from specific high-performance computer architectures and task scheduling implementations, which makes the design of generic parallel processing solutions feasible for geographical analyses.
A Multi-theory Logic Language for the World Wide Web
Authors: Giulio Piancastelli, Andrea Omicini
Venue: Proceedings of the 24th International Conference on Logic Programming (2008)

Despite the recent formalization of the Web in terms of Representational State Transfer (REST) architectural style and Resource-Oriented Architecture (ROA), current tools for Web programming generally misunderstand its design. Based on REST/ROA insights, we claim that logic languages are suited for promoting the Web architecture and principles. The mapping of REST/ROA abstractions onto elements of Contextual Logic Programming also permits runtime modification of resource behavior. In this paper we present Web Logic Programming as a Prolog-based language for the Web embedding REST/ROA principles, meant to be the basis of an application framework for rapid prototyping.
Nonlinear amygdala response to face trustworthiness: Contributions of high and low spatial frequency information
Authors: Christopher P. Said, Sean G. Baron, Alexander Todorov
Venue: Journal of Cognitive Neuroscience (2009)

Previous neuroimaging research has shown amygdala sensitivity to the perceived trustworthiness of neutral faces, with greater responses to untrustworthy compared with trustworthy faces. This observation is consistent with the common view that the amygdala encodes fear and is preferentially responsive to negative stimuli. However, some studies have shown greater amygdala activation to positive compared with neutral stimuli. The first goal of this study was to more fully characterize the amygdala response to face trustworthiness by modeling its activation with both linear and nonlinear predictors. Using fMRI, we report a nonmonotonic response profile, such that the amygdala responds strongest to highly trustworthy and highly untrustworthy faces. This finding complicates future attempts to make inferences about mental states based on activation in the amygdala. The second goal of the study was to test for modulatory effects of image spatial frequency filtering on the amygdala response. We predicted greater amygdala sensitivity to face trustworthiness for low spatial frequency images compared with high spatial frequency images. Instead, we found that both frequency ranges provided sufficient information for the amygdala to differentiate faces on trustworthiness. This finding is consistent with behavioral results and suggests that trustworthiness information may reach the amygdala through pathways carrying both coarse and fine resolution visual signals.
Cross-layer QoS mechanism for heterogeneous wireless networks
Authors: Ming-Chiao Chen, Jiann-Liang Chen, Shih-Wei Liu, Jyun-Ju Jhuo
Venue: Proceedings of the International Conference on Mobile Technology, Applications, and Systems (2008)

It is important to provide Quality of Services (QoS) in the heterogeneous wireless network environment. Cross-Layer Design could enhance the performance of the applications and achieve better QoS support. This study presents a QoS Master including QoS Daemon, QoS Agent, and System Control Model to guarantee QoS of multimedia applications in heterogeneous wireless networks. We also proposed a Cross-Layer QoS algorithm to monitor and adjust bandwidth periodically. Simulation results indicate that the average jitter, latency and packet loss are reduced respectively.
PERG-Rx: a hardware pattern-matching engine supporting limited regular expressions
Authors: Johnny Tsung Lin Ho, Guy G.F. Lemieux
Venue: Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays (2009)

PERG is a pattern matching engine designed for locating pre-defined byte string patterns (rules) from the ClamAV virus signature database in a data stream. This paper presents PERG-Rx, an extension of PERG that adds limited regular expression support for wildcard patterns used by rules that represent polymorphic viruses. To reduce the amount of state needed to track so many regular expressions, PERG-Rx employs a lossy scheme which increases the rate of false positives detected as the required state grows. The scalability and dynamic updatability of the PERG-Rx architecture to database updates are also evaluated.
Application and development of biologically plausible neural networks in a multiagent artificial life system
Authors: Marvin Oliver Schneider, Jo&#x00e3;o Lu&#x00ed;s Garcia Rosa
Venue: Neural Computing and Applications (2009)

The present article introduces the system BioAnt, which is a computational simulation of a small colony of ants (up to 99 members) in which every ant relies on a biologically more plausible artificial neural networks as control mechanism for guidance. The environment, in which the ants are placed, is three-dimensional, consisting of the anthill, sugar, water, earth elevations, walls and predators. The ants&#x2019; foraging behavior was successfully implemented as well as some basic defense mechanisms. Typical sensors and actuators of ants were modeled and the efficiency of the connectionist approach has been validated by the comparison with a simple symbolical approach. Apart from several surprising results on technical details, which are reported, the present approach clearly demonstrates the feasibility of such an implementation with connectionist and biologically more plausible principles, offering promising perspectives as a basis for further artificial life systems.
The GRAFIX I image processing system
Authors: Arnold K. Griffith
Venue: Proceedings of the May 6-10, 1974, national computer conference and exposition (1974)

The GRAFIX I system was developed in the late 1960's as a fast flexible system for processing and analyzing filmed images, particularly of material which is essentially binary (black and white), such as printed text, line drawings, certain biomedical images, fingerprints, etc. It incorporates a large scale general purpose time shared computer to provide the facilities for the efficient development of algorithms necessary to perform various image processing and analysis tasks. In addition it contains a fast, high resolution flying-spot film scanner and a powerful and rather general slave processor (the binary image processor, or BIP) which provide data collection and manipulation facilities adequate to perform image processing and analysis tasks at commercially practical speeds. So far it has been successfully employed in a commercial environment to the reading of printed multifont text in complex page formats, and to the reading of Cyrillic, Greek and even handprinted text. At present we are considering future applications beyond the area of optical character recognition, particularly the analysis of engineering drawings, as well as the automatic analysis and classification of fingerprints, the analysis of biomedical images such as chromosomes, the analysis of x-ray images, and the analysis of satellite imagery data, among others.
Reservation price reporting mechanisms for online negotiations
Authors: Seungwoo Kwon, Byungjoon Yoo, Jinbae Kim, Wei Shang, Gunwoong Lee
Venue: Decision Support Systems (2009)

To facilitate online negotiations, this paper proposes a reservation price reporting mechanism (RPR) and its extended version (ERPR), in which negotiators are invited to report their reservation price to a third-party system before initiating negotiations. Analyses using analytical models show that sellers and buyers report their true reservation prices under certain conditions with respect to the back-dragging costs. Analytical models also show that total social welfare can be increased by two reservation price reporting mechanisms. Then lab experiments are conducted to compare the performance of RPR, ERPR and the traditional direct bargaining (TDB). Consistent with the analytical models, results of the lab experiments show that RPR and ERPR reduce the number of negotiation rounds before reaching an agreement and increase negotiators' social welfare. These lab results testify to the efficiency of RPR and ERPR over TDB.
Searching for a lion in the desert: optics-based acquisition algorithms for wireless sensor networks
Authors: Shlomi Arnon, Shlomi Dolev, Ronen Kat, Debbie Kedar
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (2009)

In this paper we address the task of locating and mapping sensor nodes equipped with passive optical transmitters deployed within a wireless sensor network. The passive transmitter is in the form of a modulatable corner cube retro-reflector (CCR) and is interrogated by a base station equipped with a variable sized laser beam prior to data harvesting using optical wireless communication. We propose and discuss an efficient acquisition algorithm based on the binary search concept and evaluate its performance in locating a solitary sensor node. We demonstrate the use of an analytical tool for assessing the acquisition cost for different error probability distributions and search regimes. The common line-of-sight (LOS) requirement for both sensor location and data harvesting renders the need for individual sensor node identification redundant and thus yields a simplified search regime by comparison with previously published research on node localisation.
Lightweight secure PUFs
Authors: Mehrdad Majzoobi, Farinaz Koushanfar, Miodrag Potkonjak
Venue: Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design (2008)

To ensure security and robustness of the next generation of Physically Unclonable Functions (PUFs), we have developed a new methodology for PUF design. Our approach employs integration of three key principles: (i) inclusion of multiple delay lines for creation of each response bit; (ii) transformations and combination of the challenge bits; and (iii) combination of the outputs from multiple delay lines; to create modular, easy to parameterize, secure and reliable PUF structures. Statistical analysis of the new structure and its comparison with existing PUFs indicates a significantly lower predictability, and higher resilience against circuit faults, reverse engineering and other security attacks.
Experimental Evaluation of the Value of Structure: How to Efficiently Exploit Interdependencies in Sequence Labeling
Authors: Guillaume Wisniewski, Patrick Gallinari
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

Many problems in natural language processing, information extraction or bioinformatics consist in predicting a label for each element of a sequence of observations. The sequence of labels generally presents multiple dependencies that restrict the possible labels the elements can take. Therefore, relations between labels intuitively provide information valuable for the prediction. Several approaches have been proposed to take advantage of this additional information. However, experimental results show that taking relations into account does not always improve prediction performances, while it significantly increases the computational cost of both learning and prediction. In this work, we aim at both explaining these surprising results and proposing a simple but computationnaly efficient approach for labeling sequences.
Block-Iterative Algorithms for Non-negative Matrix Approximation
Authors: Suvrit Sra
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

In this paper we present new algorithms for non-negative matrix approximation (NMA), commonly known as the NMF problem. Our methods improve upon the well-known methods of Lee \& Seung~\cite{lee00} for both the Frobenius norm as well the Kullback-Leibler divergence versions of the problem. For the latter problem, our results are especially interesting because it seems to have witnessed much lesser algorithmic progress as compared to the Frobenius norm NMA problem. Our algorithms are based on a particular \textbf {block-iterative} acceleration technique for EM, which preserves the multiplicative nature of the updates and also ensures monotonicity. Furthermore, our algorithms also naturally apply to the Bregman-divergence NMA algorithms of~\cite{suv.nips}. Experimentally, we show that our algorithms outperform the traditional Lee/Seung approach most of the time.
A copper-dielectric cap interface with high resistance to electromigration for high performance semiconductor devices
Authors: J. Hohage, M. U. Lehr, V. Kahlert
Venue: Microelectronic Engineering (2009)

In highly integrated semiconductor devices the time to failure of copper interconnects strongly depends on the properties of the copper-dielectric cap interface. In this work a production capable preparation of copper-dielectric cap interfaces with a high resistance to electromigration (EM) has been developed for 90 and 65nm dual damascene technologies. With a new soft silicidation pretreatment of the copper metallization followed by a deposition of a SiCN or SiN cap the EM lifetime could be improved 3.5x referring to a standard SiCN capping process. The new pretreatment enables the formation of an epitaxial copper silicide layer on top of the copper metal lines which is seen as the key factor of the lifetime improvement. The new kind of cap layer process enables the lifetime improvement with only negligible increase of metal sheet resistance. The surface damage of copper and the low k inter-level dielectric which is typically caused during the copper precleaning could be minimized significantly. It is shown that there is no linear correlation between adhesion to copper and electromigration performance.