ppxscal/embedding_network huggingface dataset:
Machine condition monitoring by nonlinear feature fusion based on kernel principal component analysis with genetic algorithm
Authors: Feng Wang, Bo Cheng, Binggang Cao
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

Feature fusion can effectively utilize complementary information from different signal sources to improve the robustness of feature extractor. As most running statuses of machines are nonlinear and non-stationary, it is difficult to extract the effective features for fault diagnosis by linear feature extractor such as PCA. Therefore, a nonlinear feature fusion scheme based on kernel principal component analysis (kernel PCA) with genetic algorithm (GA) is proposed to recognize the different conditions of rolling bearing. Kernel PCA is applied to extract higher order information from a union-vector set, in which statistical features from acoustic signals and vibration signals are incorporated. The computational problem induced by the tremendous size of the feature space is also effectively settled by using a kernel function. For better classification performance, GA is applied to search the optimal parameter in kernel function. The analytical results show that the proposed feature fusion scheme can effectively improve the recognition ability of feature extractor.
Integration of Support Vector Machine with Naïve Bayesian Classifier for Spam Classification
Authors: Chui-Yu Chiu, Yuan-Ting Huang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

In this research, we propose a two-stage method for spam classification, the Naïve Bayesian Classifier (NBC) and Support Vector Machine (SVM). NBC adopts the concept of Bayesian theory for classification, and combines the conditional probability with feature count as input data for SVM which uses the radial basis function with Gaussian kernel for further classification. The classification features generated from spam data set are used to train and test the proposed method. The results are compared with other well-known classification methods to verify the performance of our proposed classifier based on the precision and recall rate.
Dna computation: Theory, practice, and prospects
Authors: Carlo C. Maley
Venue: Evolutionary Computation (1998)

L. M. Adleman launched the field of DNA computing with a demonstration in 1994 that strands of DNA could be used to solve the Hamiltonian path problem for a simple graph. He also identified three broad categories of open questions for the field. First, is DNA capable of universal computation? Second, what kinds of algorithms can DNA implement? Third, can the error rates in the manipulations of the DNA be controlled enough to allow for useful computation? In the two years that have followed, theoretical work has shown that DNA is in fact capable of universal computation. Furthermore, algorithms for solving interesting questions, like breaking the Data Encryption Standard, have been described using currently available technology and methods. Finally, a few algorithms have been proposed to handle some of the apparently crippling error rates in a few of the common processes used to manipulate DNA. It is thus unlikely that DNA computation is doomed to be only a passing curiosity. However, much work remains to be done on the containment and correction of errors. It is far from clear if the problems in the error rates can be solved sufficiently to ever allow for general-purpose computation that will challenge the more popular substrates for computation. Unfortunately, biological demonstrations of the theoretical results have been sadly lacking. To date, only the simplest of computations have been carried out in DNA. To make significant progress, the field will require both the assessment of the practicality of the different manipulations of DNA and the implementation of algorithms for realistic problems. Theoreticians, in collaboration with experimentalists, can contribute to this research program by settling on a small set of practical and efficient models for DNA computation.
Type nanotheories: a framework for term comparison
Authors: John Prager, Sarah Luger, Jennifer Chu-Carroll
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

We present in this paper Type Nanotheories (TN), a framework for representing the knowledge necessary for performing similarity comparisons between pairs of terms of the same type. TN itself uses another methodology, namely Support Outcomes, which is also introduced. Many IR and NLP applications use redundancy as a factor to increase confidence, and TN-based comparisons can determine redundancy better than simple string comparisons. Results include a showing of a 14% increase in Confidence-Weighted Score for an end-to-end QA system and an up to 68% improvement over baseline in an answer-key equivalencing experiment.
Fuzzy Support Vector Machine Based on Vague Sets for Credit Assessment
Authors: Yan-You Hao, Zhong-Xian Chi, De-Qin Yan
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

Credit assessment is one of important tools help financial institutions to hedge the credit risks. Support vector machine and fuzzy support vector machine have been applied in Credit assessment field. Fuzzy support vector machine (FSVM) does not treat equally the input point. It improves the generalization power of traditional SVM by applying a fuzzy membership to each input data point. In this paper, we propose a new FSVM based on vague sets that apply a truth-membership and a false- membership to each data point of training sets. In order to verity the effectiveness of the new FSVM, a real case of home loan data sets is given and the experimental results show that the model is promising.
Magallanes: 3D navigation for everybody
Authors: María J. Abásolo, José Mariano Della
Venue: Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia (2007)

Although the problem of wayfinding in virtual worlds has been studied in several works, it still remains as one of the main limitations of using 3d worlds in internet. This paper presents a VRML prototype, called Magallanes, that can be added to any new or existent 3D scene to help users in 3D navigation. The designer can define both viewpoints as usual and also virtual tours as connections between viewpoints. The prototype automatically generates a graphical user interface added to the scene that facilitates the selection of places of interest. When the user selects a destination, the prototype automatically finds the optimal navigation path from the avatar position to the destination, by applying the A* algorithm to the graph of viewpoints. Afterwards, the camera is animated following the generated path. One of Magallanes' novelties is that the viewpoints and connections can not only be added by prototype instantiation, but also can be dynamically done while the user navigates. Although Magallanes can be used to help any user to navigate a VRML scene, we find it particularly useful for persons with hands disabilities to whom 3D navigation with a conventional mouse may become almost impossible. Magallanes was tested in combination with a visual-based interface that captures facial gestures and head movement to control the mouse.
A Study of High-Resolution Timing
Authors: D. B. Wortman
Venue: IEEE Transactions on Software Engineering (1976)

This correspondence describes an experimental comparison of timing information provided by a large multiprogramming operating system (OS/360 MVT) with timing information derived directly from a high-resolution hardware clock. The hardware clock was found to be a superior source of timing information.
Towards a definition of an Image Ontology
Authors: Antonio Penta, Antonio Picariello, Letizia Tanca
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

Archiving, organizing, and searching multimedia data in an appropriate fashion is a task of increasing importance. The ontology theory may be appropriately extended in order to face this challenging issue. In this paper we propose an extension of an Image Database model based on NF^2 with an Ontology model. We first describe NF^2 and the main concepts of Image Ontologies, then we propose a general architecture for supporting creation and management of multimedia objects.
Gröbner bases and the number of Latin squares related to autotopisms of order ≤7
Authors: R. M. Falcón, J. Martín-Morales
Venue: Journal of Symbolic Computation (2007)

Latin squares can be seen as multiplication tables of quasigroups, which are, in general, non-commutative and non-associative algebraic structures. The number of Latin squares having a fixed isotopism in their autotopism group is at the moment an open problem. In this paper, we use Grobner bases to describe an algorithm that allows one to obtain the previous number. Specifically, this algorithm is implemented in Singular to obtain the number of Latin squares related to any autotopism of Latin squares of order up to 7.
Detecting eye fixations by projection clustering
Authors: Thierry Urruty, Stanislas Lew, Nacim Ihadaddene, Dan A. Simovici
Venue: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) (2007)

Eye movements are certainly the most natural and repetitive movement of a human being. The most mundane activity, such as watching television or reading a newspaper, involves this automatic activity which consists of shifting our gaze from one point to another. Identification of the components of eye movements (fixations and saccades) is an essential part in the analysis of visual behavior because these types of movements provide the basic elements used by further investigations of human vision. However, many of the algorithms that detect fixations present a number of problems. In this article, we present a new fixation identification technique that is based on clustering of eye positions, using projections and projection aggregation applied to static pictures. We also present a new method that computes dispersion of eye fixations in videos considering a multiuser environment. To demonstrate the performance and usefulness of our approach we discuss our experimental work with two different applications: on fixed image and video.
An adaptive fuzzy rule extraction using hybrid model of the fuzzy self-organizing map and the genetic algorithm with numerical chromosomes
Authors: Tatsuya Nomura, Tsutomu Miyoshi
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (1998)

In this paper, we propose a hybrid model of the fuzzified Kohonen's Self-Organizing Map and the Genetic Algorithms with numerical chromosomes, and automatic fuzzy rule extraction method that uses our model. The results show the possibility of superiority of our hybrid model in a Lamarckian stance to both of the individual models in cases where there is a tendency for data to change dynamically and quickly.
Assessing the Usability of Human-Computer Interfaces
Authors: T. E. Lindquist
Venue: IEEE Software (1985)

Engineers may be able to design a better interface if they take into account the control structures underlying the interface syntax.
Towards P2P-routed IF overlay networks for grid virtual machines
Authors: A. Agrawal, A. Ganguly, P. O. Boykin, R. J. Figueiredo
Venue: Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium (2005)

Grid technologies provide a valuable solution for distributed scientific applications but are not readily available for the 4th Generation Languages (4GLs) widely used in physics, climate modeling and medicine. Examples of 4GLs are interactive data language (IDL) and MATLAB. There is a need for tools allowing 4GLs to interoperate with the grid. This paper describes our design and the status of the tools under development, which include IDL bindings for Web services and tools for running and managing parallel and serial IDL processes on grids and clusters.
In Our Time: Annie and the Boys
Authors: David Alan Grier
Venue: Computer (2007)

More than any other piece of software, the spreadsheet demonstrated that the personal computer could be a useful business tool.
Automatic Speech Recognition-Putting It to Work in Industry
Authors: J. R. Welch
Venue: Computer (1980)

The advent of faster isolated-and connected-word recognizers will dramatically increase cost-effective applications of automatic speech recognition. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Comparing Costs and Benefits of Different Test Strategies for a Software Product Line: A Study from Testo AG
Authors: Dharmalingam Ganesan, Jens Knodel, Ronny Kolb, Uwe Haury, Gerald Meier
Venue: Proceedings of the 11th International Software Product Line Conference (2007)

Quality assurance in general and testing in particular remains as an unsolved problem in product line engineering. It is unclear, from an economic point of view, whether one should test each product line member separately or test just product-specific parts and compose them with tested core assets from family engineering. While the former strategy introduces redundancy in testing, the latter strategy is also more difficult because of genericity. Ideally, we need to carefully calculate cost-benefits of both cases and define a test strategy accordingly. Currently, there is no economic model for testing in the context of product lines. Thus, we introduce an initial economic model, and then perform Monte-Carlo simulations to calculate cost-benefit of the two test strategies. For the Testo product line of climate and flue gas measurement devices, the results showed that, using an infrastructure-focused test strategy, on average a cost saving of 13% can be expected with 87% certainty.
Palmprint verification based on principal lines
Authors: De-Shuang Huang, Wei Jia, David Zhang
Venue: Pattern Recognition (2008)

In this paper, we propose a novel palmprint verification approach based on principal lines. In feature extraction stage, the modified finite Radon transform is proposed, which can extract principal lines effectively and efficiently even in the case that the palmprint images contain many long and strong wrinkles. In matching stage, a matching algorithm based on pixel-to-area comparison is devised to calculate the similarity between two palmprints, which has shown good robustness for slight rotations and translations of palmprints. The experimental results for the verification on Hong Kong Polytechnic University Palmprint Database show that the discriminability of principal lines is also strong.
Detecting and Reducing Partition Nodes in Limited-routing-hop Overlay Networks
Authors: Zhenhua Li, Guihai Chen
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

Many Internet applications use overlay networks as their basic facilities, like resource sharing, collaborative computing, and so on. Considering the communication cost, most overlay networks set limited hops for routing messages, so as to restrain routing within a certain scope. In this paper we describe partition nodes in such limitedrouting- hop overlay networks, whose failure may potentially lead the overlay topology to be partitioned so that seriously affect its performance. We propose a proactive, distributed method to detect partition nodes and then reduce them by changing them into normal nodes. The results of simulations on both real-trace and generated topologies, scaling from 500 to 10000 nodes, show that our method can effectively detect and reduce partition nodes and improve the connectivity and fault tolerance of overlay networks.
System-platforms-based SystemC TLM design of image processing chains for embedded applications
Authors: Muhammad Omer Cheema, Lionel Lacassagne, Omar Hammami
Venue: EURASIP Journal on Embedded Systems (2007)

Intelligent vehicle design is a complex task which requires multidomains modeling and abstraction. Transaction-level modeling (TLM) and component-based software development approaches accelerate the process of an embedded system design and simulation and hence improve the overall productivity. On the other hand, system-level design languages facilitate the fast hardware synthesis at behavioral level of abstraction. In this paper, we introduce an approach for hardware/software codesign of image processing applications targeted towards intelligent vehicle that uses platform-based SystemC TLM and component-based software design approaches along with HW synthesis using SystemC to accelerate system design and verification process. Our experiments show the effectiveness of our methodology.
The Design of Backend Classifiers in PPRLM System for Language Identification
Authors: Hongbin Suo, Ming Li, Tantan Liu, Ping Lu, YongHong Yan
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

The design approach for classifying the backend features of the PPRLM (Parallel Phone Recognition and Language Modeling) system is demonstrated in this paper. A variety of features and their combinations extracted by language dependent recognizers were evaluated based on the National Institute of Standards and Technology (NIST) Language Recognition Evaluation (LRE) 2003 corpus. Three well-known classifiers: Gaussian Mixture Model (GMM), Support Vector Machine (SVM), and feedforward neural network (NN) are proposed to compartmentalize these high level features which are generated by n-gram language model scoring and one pass decoding based on acoustic model in PPRLM system. Finally, the log-likelihood radio (LLR) normalization is applied to backend processing to the target language scores and the performance of language recognition is enhanced.
Nanofabric PLA architecture with Redundancy Enhancement
Authors: Mandar V. Joshi, Waleed K. Al-Assadi
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

Fundamental electronic structures such as Diodes and FETs have been shown to be constructed using selectively doped semiconducting Carbon Nanotubes or Silicon Nanowires (CNTs, SiNWs) at nanometer scale. Memory and Logic cores have been proposed, that use the configurable junctions in 2-D crossbars of CNTs. These Memory and Logic arrays at this scale exhibit a significant amount of defects that account for poor a yield. Configuration of these devices in the presence of defects demands an overhead in terms of area and programming time. This work introduces a PLA configuration that makes use of fixed and adaptive redundancy in terms of the number of nanowires. This is done in order to simplify the process of programming the PLA, increase the yield, reduce the time complexity, and in turn, reduce the cost of the system.
Fuzzy scheduling on two-machine flow shop
Authors: Tzung-Pei Hong, Tzung-Nan Chuang
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (1998)

Scheduling consists mainly of allocating resources to jobs over time under necessary constraints. In the past, the processing time for each job was usually assigned or estimated as a fixed value. In many real-world applications, however, job processing time may vary dynamically with the situation. In this paper, fuzzy concepts are applied to Johnson algorithm for managing uncertain scheduling. Given a set of jobs, each having two tasks that must be executed on two machines, and their processing time membership functions, the fuzzy Johnson algorithm can yield a scheduling result with a membership function for the final completion time, thus helping managers gain a broader overall view of scheduling. Also, the conventional Johnson algorithm is shown as a special case of the fuzzy Johnson algorithm with special membership functions being assigned. The fuzzy Johnson algorithm is thus a feasible solution for both deterministic and uncertain scheduling.
Group Delay Based Approach for Frequency Estimation in Complex Noises
Authors: Lihua Fu, Hongwei Li, Meng Zhang, Yuantong Shen
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

A novel approach for frequency estimation of one-dimensional harmonics in multiplicative and additive noises is presented. To alleviate the resolution limitation of the traditional cumulant-based algorithms, group delay (GD) function is utilized. In this new approach, GD is applied to the 2nd order time-varying cumulants of harmonics in complex noises, called as the 2nd order CGD. For a given frequency estimation problem, this paper derives a simple and practical algorithm. Numerical results show that the sharp peak and high resolution property of GD preserved, which outperform some traditional methods greatly.
Sample Path Analysis of Busy Periods and Related First Passages of a Correlated MEP/MEP/1 System
Authors: Chaitanya Garikiparthi, Appie van de Liefvoort, Kenneth Mitchell
Venue: Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems (2007)

In this paper we study the busy period of an MEP/MEP/1 system, where both the arrival and the service processes can be serially correlated Matrix Exponential Processes. A dynamic programming algorithm is given to compute the probabilities for serving n customers in a busy period and expressions for the first two moments are derived. We study both the effect of correlation in the arrival and service processes and the squared coefficient of variation on these probabilities. The solutions give us qualitative insights into the nature of the busy period of the MEP/MEP/1 system. The resulting algorithms are easily programmable and efficient.
Special Feature: A Taxonomy for Valid Test Workload Generation
Authors: S. A. Mamrak
Venue: Computer (1979)

Sound workload generation methodologies have been developed for only a few evaluation environments. For the remainder, only ad hoc methods of limited applicability are available.
Using Dempster---Shafer to incorporate knowledge into satellite image classification
Authors: Bilal Al Momani, Sally Mcclean, Philip Morrow
Venue: Artificial Intelligence Review (2006)

Remote sensing imaging techniques make use of data derived from high resolution satellite sensors. Image classification identifies and organises pixels of similar spatial distribution or similar statistical characteristics into the same spectral class (theme). Contextual data can be incorporated, or `fused', with spectral data to improve the accuracy of classification algorithms. In this paper we use Dempster---Shafer's theory of evidence to achieve this data fusion. Incorporating a Knowledge Base of evidence within the classification process represents a new direction for the development of reliable systems for image classification and the interpretation of remotely sensed data.