ppxscal/embedding_network huggingface dataset:
Study and fabrication of maximum operating frequency of SAW filters as using I-line source
Authors: Fu-Der Lai, Jui-Ming Hua, H. M. Huang
Venue: Proceedings of the 6th WSEAS International Conference on Applied Electromagnetics, Wireless and Optical (2008)

In this work, the unbalance structure technique has been studied in detail. The maximum operating frequency is limited by the gap width of the SAW filter but independent of the line width. The MOF is around 27/40 times acoustic wave velocity/the gap width. Using the I-line lithography, the gap width of 0.35 µm can be easily defined. MOF of more than 7 GHz could be achieved. The near field phase shift photolithography has the potential to fabricate the SAW devices with the nano-gap width. The NFPSL could have the potential to fabricate the SAW filter with more than 27 GHz operating frequency when using I-line light source.
A bibliometric analysis of pharmacology and pharmacy journals: Scopus versus Web of Science
Authors: Juan Gorraiz, Christian Schloegl
Venue: Journal of Information Science (2008)

Our study examines the suitability of Scopus for bibliometric analyses in comparison with the Web of Science (WOS). In particular we want to explore if the outcome of bibliometric analyses differs between Scopus and WOS and, if yes, in which aspects. Since journal indicators vary among disciplines, we analysed only journals from the subject pharmacy and pharmaceutical sciences. Nonetheless, our study has also broader implications. Its major findings are: (a) Each top-100 JCR pharmacy journal was covered by Scopus. (b) The impact factor was higher for 82 and the immediacy index greater for 78 journals in Scopus in 2005. Pharmacy journals with a high impact factor in the JCR usually have a high impact factor in Scopus. (c) Several medium impact journals could be identified in Scopus which were not reported in JCR. (d) The two databases differed in the number of articles within a tolerable margin of deviation for most journals.
A PTAS for the k-Consensus Structures Problem Under Euclidean Squared Distance
Authors: Shuai Cheng Li, Yen Kaow Ng, Louxin Zhang
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

In this paper we consider a basic clustering problem that has uses in bioinformatics. A structural fragment is a sequence of ¿ points in a 3D space, where ¿ is a fixed natural number. Two structural fragments f 1 and f 2 are equivalent iff under some rotation and translation . We consider the distance between two structural fragments to be the sum of the Euclidean squared distance between all corresponding points of the structural fragments. Given a set of n structural fragments, we consider the problem of finding k (or fewer) structural fragments g 1, g 2,..., g k , so as to minimize the sum of the distances between each of f 1, f 2, ..., f n to its nearest structural fragment in g 1, ..., g k . In this paper we show a PTAS for the problem through a simple sampling strategy.
Internet2's Breakthroughs for Academic Research
Authors: Adam Stone
Venue: IEEE Distributed Systems Online (2004)

Although its promise isn't fully realized, the next-generation Internet, Internet2, is getting closer to fulfilling its mission to improve quality of life, especially through academic research.
A Taxonomy of Deterministic Forgetting Automata
Authors: Jens Glöckler
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

We investigate deterministic forgetting automata, i.e., deterministic linear bounded automata which can only use the operations `move', `erase' (rewrite with a blank symbol) and `delete' (remove completely). We give a taxonomy of deterministic forgetting automata and draw comparisons to other kinds of automata (namely deterministic one-turn pushdown automata and one-way one-counter automata). 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
Online Least Squares Support Vector Machines Based on Wavelet and Its Applications
Authors: Qian Zhang, Fuling Fan, Lan Wang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

As the conventional training algorithms of least squares support vector machines (LS-SVM) are inefficient in online applications, an online learning algorithm is proposed. The online algorithm is suitable for the large data set and practical applications where the data come in sequentially. Aiming at the characteristics of signals, a wavelet kernel satisfying wavelet frames is presented. The wavelet kernel can approximate arbitrary functions in quadratic continuous integral space, hence the generalization ability of LS-SVM is improved. To illustrate its favorable performance, the wavelet based online LS-SVM (WOLS-SVM) is applied to nonlinear system identification. The simulation results show that the WOLS-SVM outperforms the existing algorithms with higher learning efficiency as well as better accuracy, and indicate its effectiveness.
Unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization
Authors: Miguel Velez-Reyes
Venue:  (2008)

In hyperspectral imaging, hundreds of images are taken at narrow and contiguous spectral bands providing us with high spectral resolution spectral signatures that can be used to discriminate between objects. In many applications, the measured spectral signature is a mixture of the object of interest, and other objects within the field of view of the sensor. To determine which objects are in the field of view of the sensor, we need to decompose the measured spectral signature in its constituents and their contribution to the measured signal. This research dealt with the unsupervised determination of the constituents and their fractional abundance in each pixel in a hyperspectral image using a constrained positive matrix factorization (cPMF). Different algorithms are presented to compute the cPMF. Tests and validation with real and simulated data show the effectiveness of the method. Application of the approach to environmental remote sensing and microscopic imaging is shown.
A Knowledge-Based Digital Dashboard for Higher Learning Institutions
Authors: Wan Maseri Mohd, Abdullah Embong, Jasni Mohd Zain
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

We propose a novel approach of knowledge discovery method by adopting dashboard concept and incorporating elements of data clustering, visualization and knowledge codification. The dashboard was designed to help the higher institution to explore the insight of student performance by analyzing significant patterns and tacit knowledge of the experts in order to improve decision making process. The system has been developed using system development life cycle (SDLC) methodology and coded in web-based and open source environment. The dashboard architecture and software are presented in this paper.
Improving SVM Performance Using a Linear Combination of Kernels
Authors: Laura Dioş, Mihai Oltean, Alexandrina Rogozan, Jean-Pierre Pecuchet
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Standard kernel-based classifiers use only a single kernel, but the real-world applications and the recent developments of various kernel methods have emphasized the need to consider a combination of multiple kernels. We propose an evolutionary approach for finding the optimal weights of a combined kernel used by the Support Vector Machines (SVM) algorithm for solving some particular problems. We use a genetic algorithm (GA) for evolving these weights. The numerical experiments show that the evolved combined kernels (ECKs) perform better than the convex combined kernels (CCKs) for several classification problems.
Parametric Linear Arithmetic over Ordered Fields in Isabelle/HOL
Authors: Amine Chaieb
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

We use higher-order logic to verify a quantifier elimination procedure for linear arithmetic over ordered fields, where the coefficients of variables are multivariate polynomials over another set of variables, we call parameters. The procedure generalizes Ferrante and Rackoff's algorithm for the non-parametric case. The formalization is based on axiomatic type classes and automatically carries over to e.g. the rational, real and non-standard real numbers. It is executable, can be applied to HOL formulae and performs well on practical examples.
Validation of Viscoelastic and Nonlinear Liver Model for Needle Insertion from in Vivo Experiments
Authors: Yo Kobayashi, Akinori Onishi, Takeharu Hoshi, Kazuya Kawamura, Makoto Hashizume, Masakatsu G. Fujie
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

This paper shows the viscoelastic and nonlinear liver model for organ model based needle insertion, in which the deformation of an organ is estimated and predicted, and the needle trajectory is decided with organ deformation taken into consideration. An organ model including detailed material characteristics is important in order to achieve the proposed method. Firstly, the material properties of the liver are modeled from the measured data and its viscoelastic characteristics are represented by differential equations, including the term of the fractional derivative. Nonlinearity in terms of the stiffness was measured, and modeled using the quadratic function of strain. Next, a solution of an FE(Finite element) model using such material properties is shown. We use the sampling time scaling property as the solution for the viscoelastic system, while the solution for a nonlinear system using the Euler method and the Modified Newton-Raphson method is also shown. Finally, the deformation of liver model is calculated and pig liver of in vivo situation is obtained from medical ultrasound equipment. Comparing the relationship between needle displacement and force on real liver and liver model, we validate the proposed model.
The flote: an instrument for people with limited mobility
Authors: Amal Dar Aziz, Chris Warren, Hayden Bursk, Sean Follmer
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

The Flote is a wind instrument designed for people with limited mobility. Past work in this area has failed to deliver the musical expressiveness expected of an instrument while maintaining the low cost required for wide adoption. Using only head movement and breath control, both calibrated to match the player's abilities, the Flote is an avenue for creative expression and an enjoyable form of physical therapy. The software is available as a free download at http://www.theflote.com, and the hardware can be easily built by anyone with minimal familiarity with circuits.
Whole-History Rating: A Bayesian Rating System for Players of Time-Varying Strength
Authors: Rémi Coulom
Venue: Proceedings of the 6th international conference on Computers and Games (2008)

Whole-History Rating (WHR) is a new method to estimate the time-varying strengths of players involved in paired comparisons. Like many variations of the Elo rating system, the whole-history approach is based on the dynamic Bradley-Terry model. But, instead of using incremental approximations, WHR directly computes the exact maximum a posteriori over the whole rating history of all players. This additional accuracy comes at a higher computational cost than traditional methods, but computation is still fast enough to be easily applied in real time to large-scale game servers (a new game is added in less than 0.001 second). Experiments demonstrate that, in comparison to Elo, Glicko, TrueSkill, and decayed-history algorithms, WHR produces better predictions. 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
JSNVA: A Java Straight-Line Drawing Framework for Network Visual Analysis
Authors: Qi Ye, Bin Wu, Bai Wang
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Although information visualization technologies are indispensable in complex data analysis, wide-spread tools still need to be developed, as successful information visualization applications often require domain-specific customization. In this paper we introduce a software framework JSNVA for network visual analysis in different applications. JSNVA has a clear architecture and supports a more systematic way of implementing different straight-line graph drawing algorithms which show different networks on different views. JSNVA can be used as a front-end for visualization and a back-end for analysis in applications, and it can be customized for different applications. To evaluate JSNVA, we will give its applications in different graph mining tasks. Through visual analyzing these networks by different interactive visualization techniques and algorithms, we can get their underlying structure intuitively and quickly.
Using Three Layer Neural Network to Compute Multi-valued Functions
Authors: Nan Jiang, Yixian Yang, Xiaomin Ma, Zhaozhi Zhang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

This paper concerns how to compute multi-valued functions using three-layer feedforward neural networks with one hidden layer. Firstly, we define strongly and weakly symmetric functions. Then we give a network to compute a specific strongly symmetric function. The number of the hidden neurons is given and the weights are 1 or -1. Algorithm 1 modifies the weights to real numbers to compute arbitrary strongly symmetric functions. Theorem 3 extends the results to compute any multi-valued functions. Finally, we compare the complexity of our network with that of binary one. Our network needs fewer neurons.
Supervised Segmentation Based on Texture Signatures Extracted in the Frequency Domain
Authors: Antonella Lillo, Giovanni Motta, James A. Storer
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

Texture identification can be a key component in Content Based Image Recognition systems. Although formal definitions of texture vary in the literature, it is commonly accepted that textures are naturally extracted and recognized as such by the human visual system, and that this analysis is performed in the frequency domain. The method presented here employs a discrete Fourier transform in the polar space to extract features, which are then classified with a vector quantizer for supervised segmentation of images into texture regions. Experiments are conducted on a standard database of test problems that show this method compares favorably with the state-of-the-art and improves over previously proposed frequency-based methods.
Design of a Digital Home Service Delivery and Management System for OSGi Framework
Authors: Taein Hwang, Hojin Park, Jin-Wook Chung
Venue: Proceedings of the 10th Asia-Pacific Network Operations and Management Symposium on Managing Next Generation Networks and Services (2007)

Digital home services have been provided separately by each service provider who has a closed service delivery infrastructure for delivering home services. Because of this, 3rd party service providers who do not have the infrastructure to deploy home services have difficulties in participating in the home network market. Also, it is difficult for 3rd party service providers to provide a control-device-specific graphic user interface to service users due to the limitation of home gateway resources. In order to solve these problems, we propose a digital home service delivery and management system for small business companies that need to provide various home services to users. Also, this system supports functions for providing a user friendly graphic user interfaces dedicated to mobile device. By using the proposed system, the service aggregator can lead the competition of 3rd party service providers in the home network service market, and help it grow rapidly.
A Five-Round Algebraic Property of the Advanced Encryption Standard
Authors: Jianyong Huang, Jennifer Seberry, Willy Susilo
Venue: Proceedings of the 11th international conference on Information Security (2008)

This paper presents a five-round algebraic property of the Advanced Encryption Standard (AES). In the proposed property, we modify twenty bytes from five intermediate values at some fixed locations in five consecutive rounds, and we show that after five rounds of operations, such modifications do not change the intermediate result and finally still produce the same ciphertext. We introduce an algorithm named &delta;, and the algorithm accepts a plaintext and a key as two inputs and outputs twenty bytes, which are used in the five-round property. We demonstrate that the &delta; algorithm has 20 variants for AES-128, 28 variants for AES-192 and 36 variants for AES-256. By employing the &delta; algorithm, we define a modified version of the AES algorithm, the &delta;AES. The &delta;AES calls the &delta; algorithm to generate twenty bytes, and uses these twenty bytes to modify the AES round keys. The &delta;AES employs the same key scheduling algorithm, constants and round function as the AES. For a plaintext and a key, the AES and the &delta;AES produce the same ciphertext.
Integration of Services Computing Curricula in Information Technology
Authors: Gordon W. Romney, Thomas M. Gatton, Albert P. Cruz, Patrick A. Kennedy
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

In existing college degree programs, modifications are imperative in the rapidly changing field of computer systems. This paper presents the progress made at an institute of higher education in modifying existing program curricula to maintain currency with existing computer technologies to provide students with critical Services Computing skills and knowledge. An overview of concepts in Services Computing applicable to academic curricula and existing programs is discussed. The curricula for existing degree programs in Information Technology, Information Systems, and Technology Management are outlined. A needs analysis of these programs, program modifications, and the conclusions of the study are presented.
Hierarchical triangular patches for terrain rendering with their matching blocks
Authors: Choong-Gyoo Lim, ByoungTae Choi
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

To efficiently represent large artificial terrains on today's graphic hardwares, we propose a new terrain rendering scheme with hierarchical triangular patches and pre-constructed match ing blocks. It renders terrain patches at different LODs(levels-of-details) according to the current visual requirement. The hierarchical structure can reduce the total number of 'draw primitive(DirectX)' calls significantly by replacing a large set of triangles with a single patch where appropriate while other conventional methods try to reduce the total number of primitives to be rendered. After the initial construction of patches, the new scheme does not re-triangulate during runtime, further enhancing its performance. We also propose a specially designed matching method to eliminate cracks on the boundaries between neighboring patches. It constructs a few matching blocks at initialization with which it replaces original patches on boundaries where cracks may occur.
Application of the self organizing maps for visual reinforcement learning of mobile robot
Authors: Hiroshi Dozono, Ryouhei Fujiwara, Takeshi Takahashi
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Recently, the camera systems becomes more available for mobile robots. But scene analysis for generating control signals is still difficult and consumes large computational power. For this problem, the control method which generates the control signals directly from the raw camera images will be effective. In this paper, we use the reinforcement learning using the camera image as input data. For the division of the states represented with camera images, self organizing map is introduced. The division of the states and learning of the control signal using reinforcement learning are executed simultaneously on the map. For examining the performance of this algorithm, we made the simulation space using OpenGL.
A Clustering Algorithm Based on Adaptive Subcluster Merging
Authors: Jiani Hu, Weihong Deng, Jun Guo
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

This paper proposes an adaptive subcluster merging (ASM) based clustering algorithm. The ASM algorithm has two stages: subcluster partition and subcluster merging. Specifically, it first applies local expanding with variance constraint to partition subclusters with uniform granularity, and then it adaptively merges the subclusters into clusters with the notion of density. Through these two stages, ASM algorithm can identify clusters of heterogeneous structures. The feasibility of the algorithm has been successfully tested on both synthetic and real-world data sets. Comparative experimental studies of various clustering algorithms are also performed. The results demonstrate that the proposed algorithm performs better than K-means, complete-link hierarchial, density-based and maximum variance algorithms.