ppxscal/embedding_network huggingface dataset:
Interpretation of hybrid generative/discriminative algorithms
Authors: Jing-Hao Xue, D. Michael Titterington
Venue: Neurocomputing (2009)

In discriminant analysis, probabilistic generative and discriminative approaches represent two paradigms of statistical modelling and learning. In order to exploit the best of both worlds, hybrid modelling and learning techniques have attracted much research interest recently, one example being the so-called hybrid generative/discriminative algorithm proposed in Raina et al. [Classification with hybrid generative/discriminative models, in: NIPS, 2003] and its multi-class extension [A. Fujino, N. Ueda, K. Saito, A hybrid generative/discriminative approach to text classification with additional information, Inf. Process. Manage. 43(2) (2007) 379-392]. In this paper, we interpret this hybrid algorithm from three perspectives, namely class-conditional probabilities, class-posterior probabilities and loss functions underlying the model. We suggest that the hybrid algorithm is by nature a generative model with its parameters learnt through both generative and discriminative approaches, in the sense that it assumes a scaled data-generation process and uses scaled class-posterior probabilities to perform discrimination. Our suggestion can also be applied to its multi-class extension. In addition, using simulated and real-world data, we compare the performance of the normalised hybrid algorithm as a classifier with that of the naive Bayes classifier and linear logistic regression. Our simulation studies suggest in general the following: if the covariance matrices are diagonal matrices, the naive Bayes classifier performs the best; if the covariance matrices are full matrices, linear logistic regression performs the best. Our studies also suggest that the hybrid algorithm may provide worse performance than either the naive Bayes classifier or linear logistic regression alone.
Software-Intensive Equipment Fault Diagnosis Research Based on D-S Evidential Theory
Authors: Peng Zhao, Xiaodong Mu, Zhaoxiang Yi, Zongrun Yin
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

Aiming at limitations of the current fault diagnosis of the software-intensive equipment (SIE), considering the advantages of D-S evidential theory at dealing with multi-information, this paper presents a method of fault diagnosis at the decision level based on D-S evidential theory. The method establishes system structure of fault diagnosis, constructs the reasonable basic probability assignment algorithm, carries out multi-criteria fusion using D-S fusion model and method. The method is proved to be effective for fault location by instance. It makes diagnosed information more definite and improves the accuracy of diagnosis.
Configurable migrating architecture for interface architecture of RT databases in mobile control system
Authors: Jindrich Cernohorsky, Roman Guzik
Venue: Proceedings of the 7th conference on Circuits, systems, electronics, control and signal processing (2008)

Current tendency in software development of large control systems with mobile devices leads to products built up from components working in different nodes of a heterogeneous network environment. Thus collaboration of particular components becomes an important aspect, since a program composed of components does not guarantee in itself reliable function after the system is extended or a component is replaced. To ensure the system reliability, it is necessary to create a middleware layer, which is able to guarantee a reliable cooperation of components in a heterogeneous distributed environment at application design level. The present paper describes an approach to the design of configurable software architecture focused in the field of mobile control systems and its databases. It introduces the technical realization of the middleware layer for reliable and predictable collaboration of components in a distributed heterogeneous industrial environment and theirs usage in databases of mobile control systems.
Mobility Management Incorporating Pattern Recognition in the Handoff Decision
Authors: Kwong Chiew Foong, Lee Sze Wei, Sim Moh Lim
Venue: Proceedings of the 2009 International Conference on Advanced Computer Control (2009)

In the age of global communications, heterogeneous networks are seen to be the best choice of strategy to ensure continuous and uninterruptible services. This will allow mobile terminal to stay in connection even they are migrating into different segment coverage through the handoff process. In the quest for efficient handoff especially in the heterogeneous environment, various techniques of handoff decision making have been used. This paper will discuss different techniques in the traditional handover decision algorithm and explore the method of handoff decision using pattern recognition method, mainly the Adaptive Network Fuzzy Inference System (ANFIS). The paper will also present results simulated in an experiment, and comparison between different handoff algorithms with respect to ANFIS.
A General Similarity Framework for Horn Clause Logic
Authors: S. Ferilli, T. M. A. Basile, M. Biba, N. Di Mauro, F. Esposito
Venue: Fundamenta Informaticae (2009)

First-Order Logic formul&aelig; are a powerful representation formalism characterized by the use of relations, that cause serious computational problems due to the phenomenon of indeterminacy (various portions of one description are possibly mapped in different ways onto another description). Being able to identify the correct corresponding parts of two descriptions would help to tackle the problem: hence, the need for a framework for the comparison and similarity assessment. This could have many applications in Artificial Intelligence: guiding subsumption procedures and theory revision systems, implementing flexible matching, supporting instance-based learning and conceptual clustering. Unfortunately, few works on this subject are available in the literature. This paper focuses on Horn clauses, which are the basis for the Logic Programming paradigm, and proposes a novel similarity formula and evaluation criteria for identifying the descriptions components that are more similar and hence more likely to correspond to each other, based only on their syntactic structure. Experiments on real-world datasets prove the effectiveness of the proposal, and the efficiency of the corresponding implementation in the above tasks.
An Introduction to Grammar Convergence
Authors: Ralf Lämmel, Vadim Zaytsev
Venue: Proceedings of the 7th International Conference on Integrated Formal Methods (2009)

Grammar convergence is a lightweight verification method for establishing and maintaining the correspondence between grammar knowledge ingrained in all kinds of software artifacts, e.g., object models, XML schemas, parser descriptions, or language documents. The central idea is to extract grammars from diverse software artifacts, and to transform the grammars until they become syntactically identical. The present paper introduces and illustrates the basics of grammar convergence.
An Adaptable-Multilayer Fractional Fourier Transform Approach for Image Registration
Authors: Wei Pan, Kaihuai Qin, Yao Chen
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

a novel adaptable accurate way for calculating Polar FFT and Log-Polar FFT is developed in this paper, named Multilayer Fractional Fourier Transform (MLFFT). MLFFT is a necessary addition to the pseudo-polar FFT for the following reasons: It has lower interpolation errors in both polar and log-polar Fourier transforms; it reaches better accuracy with the nearly same computing complexity as the pseudo-polar FFT; it provides a mechanism to increase the accuracy by increasing the user-defined computing level. This paper demonstrates both MLFFT itself and its advantages theoretically and experimentally. By emphasizing applications of MLFFT in image registration with rotation and scaling, our experiments suggest two major advantages of MLFFT: 1) scaling up to 5 and arbitrary rotation angles, or scales up to 10 without rotation can be recovered by MLFFT while currently the result recovered by the state-of-the-art algorithms is the maximum scaling of 4; 2) No iteration is needed to obtain large rotation and scaling values of images by MLFFT, hence it is more efficient than the pseudopolar-based FFT methods for image registration.
Sequential and non-sequential acceptance sampling plans for autocorrelated processes using ARMA(p,q) models
Authors: M. S. Aminzadeh
Venue: Computational Statistics (2009)

This paper presents variable acceptance sampling plans based on the assumption that consecutive observations on a quality characteristic(X) are autocorrelated and are governed by a stationary autoregressive moving average (ARMA) process. The sampling plans are obtained under the assumption that an adequate ARMA model can be identified based on historical data from the process. Two types of acceptance sampling plans are presented: (1) Non-sequential acceptance sampling: In this case historical data is available based on which an ARMA model is identified. Parameter estimates are used to determine the action limit (k) and the sample size(n). A decision regarding acceptance of a process is made after a complete sample of size n is selected. (2) Sequential acceptance sampling: Here too historical data is available based on which an ARMA model is identified. A decision regarding whether or not to accept a process is made after each individual sample observation becomes available. The concept of Sequential Probability Ratio Test (SPRT) is used to derive the sampling plans. Simulation studies are used to assess the effect of uncertainties in parameter estimates and the effect of model misidentification (based on historical data) on sample size for the sampling plans. Macros for computing the required sample size using both methods based on several ARMA models can be found on the author's web page http://pages.towson.edu/aminza/papers.html .
Resiliency Policies in Access Control
Authors: Ninghui Li, Qihua Wang, Mahesh Tripunitara
Venue: ACM Transactions on Information and System Security (TISSEC) (2009)

We introduce the notion of resiliency policies in the context of access control systems. Such policies require an access control system to be resilient to the absence of users. An example resiliency policy requires that upon removal of any s users, there should still exist d disjoint sets of users such that the users in each set together possess certain permissions of interest. Such a policy ensures that even when emergency situations cause some users to be absent, there still exist independent teams of users that have the permissions necessary for carrying out critical tasks. The Resiliency Checking Problem determines whether an access control state satisfies a given resiliency policy. We show that the general case of the problem and several subcases are intractable (NP-hard), and identify two subcases that are solvable in linear time. For the intractable cases, we also identify the complexity class in the polynomial hierarchy to which these problems belong. We discuss the design and evaluation of an algorithm that can efficiently solve instances of nontrivial sizes that belong to the intractable cases of the problem. Furthermore, we study the consistency problem between resiliency policies and static separation of duty policies. Finally, we combine the notions of resiliency and separation of duty to introduce the resilient separation of duty policy, which is useful in situations where both fault-tolerance and fraud-prevention are desired.
Review of trust and machine ethics research: towards a bio-inspired computational model of ethical trust (CMET)
Authors: Hock Chuan Lim, Rob Stocker, Henry Larkin
Venue: Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems (2008)

Recent advances in the fields of robotics, cyborg development, moral psychology, trust, multi agent-based systems and socionics have raised the need for a better understanding of ethics, moral reasoning, judgment and decision-making within the system of man and machines. Here we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the social moral norms at the collective end. We review salient works in the fields of trust and machine ethics research, underscore the importance and the need for a deeper understanding of ethical trust at the individual level and the development of collective social moral norms. Drawing upon the recent findings from neural sciences on mirror-neuron system (MNS) and social cognition, we present a bio-inspired Computational Model of Ethical Trust (CMET) to allow investigations of the interplay of ethical trust and social moral norms.
A novel radio-over-fiber system architecture with bidirectional fiber transmission for full-duplex connection
Authors: Z. Dong, J. Lu, L. Chen, J. Yu
Venue: Proceedings of the 2008 International Conference on Advanced Infocomm Technology (2008)

We have proposed and experimentally demonstrated a novel full-duplex radio-over-fiber (ROF) architecture with bi-directional fiber transmission. The downstream data are carried by a carrier-suppression dual-mode millimeter-wave signals, while the upstream baseband data will be modulated on another lightwave with the same wavelength as that of the downstream. Therefore the crosstalk caused by simulated Brillouin scattering to the downstream and upstream signal can be avoided, and bidirectional transmission can be realized. Our experimental results show well performance up to 2.5 Gb/s at 20-km reach range.
Guidelines for the use of infinite source queueing models in the analysis of computer system performance
Authors: J. P. Buzen, P. S. Goldberg
Venue: Proceedings of the May 6-10, 1974, national computer conference and exposition (1974)

Mathematical models based on queueing theory are widely used in the analysis of computer system performance. As in the case of other engineering disciplines, these models never correspond exactly to the real systems they are intended to represent. However, if the associated error terms are sufficiently small the models can still serve as valuable tools for estimating performance levels in specific cases and for studying the factors which influence overall system behavior. In this paper we examine some error terms which arise when the familiar M/G/1 queueing model is used to predict expected response times and queue lengths in systems which contain only a finite number of sources.
Empirical Paraphrasing of Modern Greek Text in Two Phases: An Application to Steganography
Authors: Katia Lida Kermanidis, Emmanouil Magkos
Venue: Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing (2009)

This paper describes the application of paraphrasing to steganography, using Modern Greek text as the cover medium. Paraphrases are learned in two phases: a set of shallow empirical rules are applied to every input sentence, leading to an initial pool of paraphrases. The pool is then filtered through supervised learning techniques. The syntactic transformations are shallow and require minimal linguistic resources, allowing the methodology to be easily portable to other inflectional languages. A secret key shared between two communicating parties helps them agree on one chosen paraphrase, the presence of which (or not) represents a binary bit of hidden information. The ability to simultaneously apply more than one rules, and each rule more than one times, to an input sentence increases the paraphrase pool size, ensuring thereby steganographic security.
Graph self-organizing maps for cyclic and unbounded graphs
Authors: M. Hagenbuchner, A. Sperduti, A. C. Tsoi
Venue: Neurocomputing (2009)

Self-organizing maps capable of processing graph structured information are a relatively new concept. This paper describes a novel concept on the processing of graph structured information using the self-organizing map framework which allows the processing of much more general types of graphs, e.g. cyclic graphs, directed graphs. Previous approaches to this problem were limited to the processing of bounded graphs, their computational complexity can grow rapidly with the level of connectivity of the graphs concerned, and are restricted to the processing of positional graphs. The novel concept proposed in this paper, namely, by using the clusters formed in the state space of the self-organizing map to represent the ''strengths'' of the activation of the neighboring vertices, rather than as in previous approaches, using the state space of the surrounding vertices to represent such ''strengths'' of activations. Such an approach resulted in reduced computational demand, and in allowing the processing of non-positional graphs.
Information architecture with IBM Task Modeler
Authors: Colin Bird, Mark Farmer
Venue: Proceedings of the 21st British HCI Group Annual Conference on HCI 2008: People and Computers XXI: HCI...but not as we know it - Volume 2 (2007)

The IBM Task Modeler supports the rapid creation and analysis of hierarchical task models, thereby providing a valuable and naturally visual tool for information architects. Task Modeler not only facilitates the essential processes of design, validation, and modification but also enables an information architect to develop and apply schemes for information classification.
Performance Consensus Problem of Multi-Agent Systems with Multiple State Variables
Authors: Naoki Hayashi, Toshimitsu Ushio
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

A consensus problem has been studied in many fundamental and application fields to analyze coordinated behavior in multi-agent systems. In a consensus problem, it is usually assumed that a state of each agent is scalar and all agents have an identical linear consensus protocol. We present a consensus problem of multi-agent systems where each agent has multiple state variables and a performance value evaluated by a nonlinear performance function according to its current state. We derive sufficient conditions for agents to achieve consensus on the performance value using an algebraic graph theory and the mean value theorem. We also consider an application of a performance consensus problem to resource allocation in soft real-time systems so as to achieve a fair QoS (Quality of Service) level.
Tile-Based Fault Tolerant Approach Using Partial Reconfiguration
Authors: Atsuhiro Kanamaru, Hiroyuki Kawai, Yoshiki Yamaguchi, Morisothi Yasunaga
Venue: Proceedings of the 5th International Workshop on Reconfigurable Computing: Architectures, Tools and Applications (2009)

This paper deals with a dependable computing system using a reconfigurable device. The work carried out for this purpose of this study involved the proposition of a fault-tolerant approach which covers microprocessors. TFT, which is short for tile-based fault tolerant approach, has the intermediate layer which makes the connection between physical circuit layout and logical circuit layout for use in partial and dynamic reconfiguration. The reconfiguration is effectively utilized for online replacement of failed circuits. An advantage of TFT is that there is no conflict with other fault-tolerant approaches, and therefore TFT is freely available in the construction of dependable systems.
Fuzzy random renewal process with queueing applications
Authors: Shuming Wang, Yan-Kui Liu, Junzo Watada
Venue: Computers Mathematics with Applications (2009)

Using extension principle associated with a class of continuous Archimedean triangular norms, this paper studies a fuzzy random renewal process in which the interarrival times are assumed to be independent and identically distributed fuzzy random variables. Some limit theorems in chance measure and in expected value for the sum of fuzzy random variables are proved on the basis of the continuous Archimedean triangular norm based arithmetics. Furthermore, we discuss the fuzzy random renewal process based on the obtained limit theorems, and derive a fuzzy random elementary renewal theorem for the long-run expected renewal rate. The renewal theorem obtained in this paper can degenerate to the corresponding classical result in stochastic renewal process. Finally, two case studies of queueing systems are provided to illustrate the application of the fuzzy random elementary renewal theorem.
The web learning system of 'Virtual eBMS': a tool supporting unstructured and just-in-time learning
Authors: Gianluca Elia, Giustina Secundo, Cesare Taurino
Venue: International Journal of Networking and Virtual Organisations (2009)

In the era of the Global, Digital and Knowledge-based Economy, a just-in-time access to learning content, as well as an efficient way to access increasingly distributed knowledge sources, is required in order to solve the problem of 'knowledge obsolescence'. In this scenario, traditional web learning systems are no longer adequate and need a strong integration with Knowledge Management (KM) systems, in order to trigger just-in-time/at workplace/customised/on-demand and unstructured learning processes, in place of an old-fashioned time/place/content predefined ones. In this paper, we describe the main pillars underpinning an innovative approach to web learning based on the above-mentioned principles. Moreover, we provide a detailed representation of the web learning component of 'Virtual eBMS', a web-based system designed and implemented at the e-Business Management Section of the Scuola Superiore ISUFI, University of Salento (Italy). In particular, we describe the content-oriented and the service-oriented perspectives of the implemented system by highlighting its innovative elements with respect to a traditional web learning system.
Parallel placement for FPGAs revisited
Authors: Cristinel Ababei
Venue: Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays (2009)

The runtime of classic sequential placement algorithms for FPGAs continues to represent a serious problem, aggravated by the continuous increase of FPGAs. The traditional way to parallelize the placement step is to use parallel distributed implementations run on a network of processors. This approach can suffer from significant communication and synchronization runtime overheads. To address that, we propose the use of multithreading for parallelization. The top level placement problem is decomposed into region-based placement sub-problems using four-way min-cut partitioning. These sub-problems are then processed in parallel by worker threads. The final solution, constructed using the results from all sub-problems, is further improved using a fast low-temperature annealing refinement step. Using this technique, we parallelize the simulated annealing based placement algorithm of VPR. The new parallel placement algorithm achieves an average speed-up of 2.5x using four threads, while the wirelength after placement and circuit delay after routing increased on average with 3.7% and 2.15% respectively.
Overview and Framework for Data and Information Quality Research
Authors: Stuart E. Madnick, Richard Y. Wang, Yang W. Lee, Hongwei Zhu
Venue: Journal of Data and Information Quality (JDIQ) (2009)

Awareness of data and information quality issues has grown rapidly in light of the critical role played by the quality of information in our data-intensive, knowledge-based economy. Research in the past two decades has produced a large body of data quality knowledge and has expanded our ability to solve many data and information quality problems. In this article, we present an overview of the evolution and current landscape of data and information quality research. We introduce a framework to characterize the research along two dimensions: topics and methods. Representative papers are cited for purposes of illustrating the issues addressed and the methods used. We also identify and discuss challenges to be addressed in future research.