ppxscal/embedding_network huggingface dataset:
Virtual Laboratory for Development and Execution of Biomedical Collaborative Applications
Authors: Marian Bubak, Tomasz Gubala, Maciej Malawski, Bartosz Balis, Wlodzimierz Funika, Tomasz Bartynski, Eryk Ciepiela, Daniel Harezlak, Marek Kasztelnik, Joanna Kocot, Dariusz Krol, Piotr Nowakowski, Michal Pelczar, Jakub Wach, Matthias Assel, Alfredo Tirado-Ramos
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

The ViroLab Virtual Laboratory is a collaborative platform for scientists representing multiple fields of expertise while working together on common scientific goals. This environment makes it possible to combine efforts of computer scientists, virology and epidemiology experts and experienced physicians to support future advances in HIV-related research and treatment. The paper explains the challenges involved in building a modern, inter-organizational platform to support science and gives an overview of solutions to these challenges. Examples of real-world problems applied in the presented environment are also described to prove the feasibility of the solution.
DHT-Based Mobile Service Discovery Protocol for Mobile Ad Hoc Networks
Authors: Eunyoung Kang, Moon Jeong Kim, Eunju Lee, Ungmo Kim
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Service discovery to search for a service available in a mobile ad-hoc network is an important issue. Although mobile computing technologies grow ever more powerful and accessible, MANET, consisting of mobile devices without any fixed infrastructure, has such features as high mobility and resource constraints. In this paper, we propose an effective service discovery protocol which is based on the concept of peer-to-peer caching of service information and DHT-based forwarding of service requests to solve these problems. Neighboring information, such as services and power is shared not only through logical neighbors but also through physically nearby neighboring nodes. Our protocol is that physical hop counts and the number of messages exchanged have been significantly reduced, since it does not require a central lookup server and does not rely on multicasting and flooding. The results of the simulation show that our proposed scheme works very well on dynamic MANET.
Learning a Frequency---Based Weighting for Medical Image Classification
Authors: Tobias Gass, Adrien Depeursinge, Antoine Geissbuhler, Henning Müller
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

This article describes the use of a frequency---based weighting developed for image retrieval to perform automatic annotation of images (medical and non---medical). The techniques applied are based on a simple tf/idf (term frequency, inverse document frequency) weighting scheme of GIFT (GNU Image Finding Tool), which is augmented by feature weights extracted from training data. The additional weights represent a measure of discrimination by taking into account the number of occurrences of the features in pairs of images of the same class or in pairs of images from different classes. The approach is fit to the image classification task by pruning parts of the training data. Further investigations were performed showing that weightings lead to significantly worse classification quality in certain feature domains. A classifier using a mixture of tf/idf weighted scoring, learned feature weights, and regular Euclidean distance gave best results using only the simple features. Using the aspect---ratio of images as feature improved results significantly.
Book Revievws
Venue: IEEE Computer Graphics and Applications (1983)

This book is at once a delight and a disappointment. In the chapters that focus on robots, Chapters 8-12, the book is crisp and clear, informative, educational, and imaginative. These chapters appear to be the author's native ground. 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
Performance And Availability in a Network File Server
Authors: William Jackson, Paul Rogers, Robert Hearn, Jeffrey Mattiace
Venue: IEEE Micro (1986)

A network for a critical application keeps its performance high and its downtime low. How did its designers enable it to do both?
Towards robust semantic role labeling
Authors: Sameer S. Pradhan, Wayne Ward, James H. Martin
Venue: Computational Linguistics (2008)

Most semantic role labeling (SRL) research has been focused on training and evaluating on the same corpus. This strategy, although appropriate for initiating research, can lead to overtraining to the particular corpus. This article describes the operation of assert, a state-of-the art SRL system, and analyzes the robustness of the system when trained on one genre of data and used to label a different genre. As a starting point, results are first presented for training and testing the system on the PropBank corpus, which is annotated Wall Street Journal (WSJ) data. Experiments are then presented to evaluate the portability of the system to another source of data. These experiments are based on comparisons of performance using PropBanked WSJ data and PropBanked Brown Corpus data. The results indicate that whereas syntactic parses and argument identification transfer relatively well to a new corpus, argument classification does not. An analysis of the reasons for this is presented and these generally point to the nature of the more lexical/semantic features dominating the classification task where more general structural features are dominant in the argument identification task.
Practical and Theoretical Issues for the Computation of Generalized Critical Values of a Polynomial Mapping
Authors: Mohab Safey El Din
Venue: Computer Mathematics: 8th Asian Symposium, ASCM 2007, Singapore, December 15-17, 2007. Revised and Invited Papers (2008)

Let be a polynomial of degree D. Computing the set of generalized critical values of the mapping (i.e. ) is an important step in algorithms computing sampling points in semi-algebraic sets defined by a single inequality.A previous algorithm allows us to compute the set of generalized critical values of $\widetilde{f}$. This one is based on the computation of the critical locus of a projection on a plane P. This plane P must be chosen such that some global properness properties of some projections are satisfied. These properties, which are generically satisfied, are difficult to check in practice. Moreover, choosing randomly the plane P induces a growth of the coefficients appearing in the computations.We provide here a new certified algorithm computing the set of generalized critical values of $\widetilde{f}$. This one is still based on the computation of the critical locus on a plane P. The certification process consists here in checking that this critical locus has dimension 1 (which is easy to check in practice), without any assumption of global properness. Moreover, this allows us to limit the growth of coefficients appearing in the computations by choosing a plane P defined by sparse equations. Additionally, we prove that the degree of this critical curve is bounded by $(D-1)^{n-1}-\mathfrak{d}$ where $\mathfrak{d}$ is the sum of the degrees of the positive dimensional components of the ideal $\langle \frac{\partial f}{\partial X_1}, \ldots,\frac{\partial f}{\partial X_n}\rangle$.We also provide complexity estimates on the number of arithmetic operations performed by a probabilistic version of our algorithm.Practical experiments at the end of the paper show the relevance and the importance of these results which improve significantly in practice previous contributions.
Constrained Cascade Generalization of Decision Trees
Authors: Huimin Zhao, Sudha Ram
Venue: IEEE Transactions on Knowledge and Data Engineering (2004)

While decision tree techniques have been widely used in classification applications, a shortcoming of many decision tree inducers is that they do not learn intermediate concepts, i.e., at each node, only one of the original features is involved in the branching decision. Combining other classification methods, which learn intermediate concepts, with decision tree inducers can produce more flexible decision boundaries that separate different classes, potentially improving classification accuracy. We propose a generic algorithm for cascade generalization of decision tree inducers with the maximum cascading depth as a parameter to constrain the degree of cascading. Cascading methods proposed in the past, i.e., loose coupling and tight coupling, are strictly special cases of this new algorithm. We have empirically evaluated the proposed algorithm using logistic regression and C4.5 as base inducers on 32 UCI data sets and found that neither loose coupling nor tight coupling is always the best cascading strategy and that the maximum cascading depth in the proposed algorithm can be tuned for better classification accuracy. We have also empirically compared the proposed algorithm and ensemble methods such as bagging and boosting and found that the proposed algorithm performs marginally better than bagging and boosting on the average.
Applications of linear permanent magnet actuators in offshore applications
Authors: Ravindra Babu Ummaneni, J. E. Brennvoll, Robert Nilssen
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

This paper mainly describes the research concepts and application possibilities in replacing the linear hydraulic and pneumatic devices with linear permanent magnet actuators, especially in offshore field. With the recent rapid progress in permanent magnet technologies, a range of compact, flexible and high performance linear actuators are available for many applications. But even now the hydraulic devices take the major lead in many application areas where the requirement of high power density and reliability needed. To overcome the difficulty of achieving high power from linear actuators alone, a concept of double gas spring is introduced. This presentation mainly focuses on the summarizing the application areas that are suitable for replacing hydraulic devices with linear permanent actuator based on gas spring concepts.
User-Centered Design of Web Pages
Authors: Chung-Hsing Yeh, Yang-Cheng Lin
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

This paper conducts an experimental study on university web pages to examine whether the hyperlink style affects users' feelings of a web page. We categorize 3 hyperlink styles, including text only, text and symbol, and text and icon. A grey relational analysis conducted suggests that the hyperlink style is a crucial element in user-centered web page design. The experimental study identifies 7 web page design elements and 33 representative webs pages as experimental samples for developing a neural network (NN) model. The NN mode is used to examine the complex relationship between 7 design elements and 3 users' feelings of web pages. With the NN model, a web page design database is built consisting of 3,645 different combinations of design elements, together with their associated feeling values. As a general rule, a web page with the "text only" hyperlinks has the highest possibility of being easiest and clearest. A web page with the "text and symbol" hyperlinks will have the most classic look, while the "text and icon" hyperlinks will make the web page have the most modern appearance. These design-supporting results provide useful insights in facilitating the user-centered web design process.
Text Particles Multi-band Fusion for Robust Text Detection
Authors: Pengfei Xu, Rongrong Ji, Hongxun Yao, Xiaoshuai Sun, Tianqiang Liu, Xianming Liu
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

Texts in images and videos usually carry important information for visual content understanding and retrieval. Two main restrictions exist in the state-of-the-art text detection algorithms: weak contrast and text-background variance. This paper presents a robust text detection method based on text particles (TP) multi-band fusion to solve there problems. Firstly, text particles are generated by their local binary pattern of pyramid Haar wavelet coefficients in YUV color space. It preserves and uniforms text-background contrasts while extracting multi-band information. Secondly, the candidate text regions are generated via density-based text particle multi-band fusion, and the LHBP histogram analysis is utilized to remove non-text regions. Our TP-based detection framework can robustly locate text regions regardless of diversity sizes, colors, rotations, illuminations and text-background contrasts. Experiment results on ICDAR 03 over the existing methods demonstrate the robustness and effectiveness of the proposed method.
Fast reversible language recognition using cellular automata
Authors: Martin Kutrib, Andreas Malcher
Venue: Information and Computation (2008)

We investigate cellular automata as acceptors for formal languages. In particular, we consider real-time devices which are reversible on the core of computation, i.e., from initial configuration to the configuration given by the time complexity. This property is called real-time reversibility. We study whether for a given real-time CA working on finite configurations with fixed boundary conditions there exists a reverse real-time CA with the same neighborhood. It is shown that real-time reversibility is undecidable, which contrasts the general case, where reversibility is decidable for one-dimensional devices. Moreover, we prove the undecidability of emptiness, finiteness, infiniteness, inclusion, equivalence, regularity, and context-freedom. First steps towards the exploration of the computational capacity are done and closure under Boolean operations is shown.
An efficient nonuniform index in the wireless broadcast environments
Authors: Jun-Hong Shen, Ye-In Chang
Venue: Journal of Systems and Software (2008)

Data broadcast is an efficient dissemination method to deliver information to mobile clients through the wireless channel. It allows a huge number of the mobile clients simultaneously access data in the wireless environments. In real-life applications, more popular data may be frequently accessed by clients than less popular ones. Under such scenarios, Acharya et al.'s Broadcast Disks algorithm (BD) allocates more popular data appeared more times in a broadcast period than less popular ones, i.e., the nonuniform broadcast, and provides a good performance on reducing client waiting time. However, mobile devices should constantly tune in to the wireless broadcast channel to examine data, consuming a lot of energy. Using index technologies on the broadcast file can reduce a lot of energy consumption of the mobile devices without significantly increasing client waiting time. In this paper, we propose an efficient nonuniform index called the skewed index, SI, over BD. The proposed algorithm builds an index tree according to skewed access patterns of clients, and allocates index nodes for the popular data more times than those for the less popular ones in a broadcast cycle. From our experimental study, we have shown that our proposed algorithm outperforms the flexible index and the flexible distributed index.
Agent-Grid Integration Language
Authors: Clement Jonquet, Pascal Dugenie, Stefano A. Cerri
Venue: Multiagent and Grid Systems (2008)

The GRID and MAS (Multi-Agent Systems) communities believe in the potential of GRID and MAS to enhance each other as these models have developed significant complementarities. Thus, both communities agree on the 'what' to do: promote an integration of GRID and MAS models. However, while the 'why' to do it has been stated and assessed, the 'how' to do it remains a research problem. This paper addresses this problem by means of a service-oriented approach. Services are exchanged (i.e., provided and used) by agents through GRID mechanisms and infrastructure. The paper first consists of a set of states of the art about integration approaches in GRID, MAS and Service-Oriented Computing (SOC). It secondly proposes a model for GRID-MAS integrated systems. Concepts, relations between them and rules are semantically described by a set-theory formalization and a common graphical description language, called Agent-Grid Integration Language (AGIL). This language may be used to describe future GRID-MAS integrated systems. AGIL's concepts are directly influenced by OGSA (Open Grid Service Architecture) and the STROBE agent communication and representation model.
Distributed Frequent Closed Itemsets Mining
Authors: Chun Liu, Zheng Zheng, Kai-Yuan Cai, Shichao Zhang
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

As many large organizations have multiple data sources and the scale of dataset becomes larger and larger, it is inevitable to carry out data mining in the distributed environment. In this paper, we address the problem of mining global frequent closed itemsets in distributed environment. A novel algorithm is proposed to obtain global frequent closed itemsets with exact frequency and it is shown that the algorithm can determine all the global frequent closed itemsets. A new data structure is developed to maintain the closed itemsets. Then an efficient implementation is provided based on the structure. Experimental results show that the proposed algorithm is effective.
Upper Semilattices in Many-One Degrees
Authors: Sergei Podzorov
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

The paper gives an overview over recent results of the author on various upper semilattices of many-one degrees. The local isomorphism type (i.e. the collection of isomorphism types of all principal ideals) of m-degrees belonging to any fixed class of arithmetical hierarchy is completely described. The description of the semilattices of simple, hypersimple and $\Delta^0_2$ m-degrees up to isomorphism is also given.
Financial Time Series Analysis of SV Model by Hybrid Monte Carlo
Authors: Tetsuya Takaishi
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

We apply the hybrid Monte Carlo (HMC) algorithm to the financial time sires analysis of the stochastic volatility (SV) model for the first time. The HMC algorithm is used for the Markov chain Monte Carlo (MCMC) update of volatility variables of the SV model in the Bayesian inference. We compute parameters of the SV model from the artificial financial data and compare the results from the HMC algorithm with those from the Metropolis algorithm. We find that the HMC decorrelates the volatility variables faster than the Metropolis algorithm. We also make an empirical analysis based on the Yen/Dollar exchange rates.
Backstepping Control of Uncertain Time Delay Systems Based on Neural Network
Authors: Mou Chen, Chang-Sheng Jiang, Qing-Xian Wu, Wen-Hua Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In this paper, a robust adaptive control scheme is proposed for a class of uncertain MIMO time delay systems based on backstepping method with Radical basis function(RBF) neural network. The system uncertainty is approximated by RBF neural networks, and a parameter update law is presented for approximating the system uncertainty. In each step, the control scheme is derived in terms of linear matrix inequalities (LMI's). A robust adaptive controller is designed using backstepping and LMI method based on the output of the RBF neural networks. Finally, an example is given to illustrate the availability of the proposed control scheme.
Image Segmentation by Nonparametric Color Clustering
Authors: Shukui Bo, Yongqiang Ma, Chongguang Zhu
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

We present a color image segmentation scheme based on pixel color clustering. The proposed segmentation is based on mean shift clustering method, which is a powerful tool for the analysis of feature space. However, earlier clustering techniques based on mean shift use single scale over the entire feature space and are not feasible to analyze complex multi-modal feature spaces. In this paper, we present an adaptive mean shift method, in which the local scale information is involved. Actual regions in an image can be obtained by segmentation using the proposed clustering technique.
Conjiont-based student-centered education in primary and secondary schools
Authors: Chan Jung Park, Jung Suk Hyun
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

The advance of e-learning accelerates the development of student-centered educational methods that consider the characteristics and the requirements of students. A lot of researches for developing new instructional methods and materials have been progressed actively. If the efficient instructional methods that satisfy students' requirements are proposed, better educational effects could be achieved. In this paper, in order to analyze students' needs and teachers' needs and to include their needs to instructions, we choose Cyberethics education as a target subject because Cyberethics education has become a hot topic in education arena these days. We firstly decompose instructional design attributes into 4 components such as goal, model, content, and media in order to analyze students' needs in Cyberethics education. And then, we figure out the relative importance among 4 components and the best combination of the instructional design attributes for students and for teachers by using Conjoint analysis. Next, in order to analyze any difference in students' learning achievements and their satisfaction levels, we give the same lecture but different instructional methods to two groups. And then, we compare the differences between two groups in terms of the learning achievements, and the satisfaction levels.
Adaptive quantization of wavelet packet coefficients for image watermarking
Authors: Chi-Man Pun, I-Kuan Kong
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

In this paper, a robust digital image watermarking approach using adaptive quantization of wavelet packet coefficients was proposed. The original image is decomposed by discrete wavelet packet transform and the dominant wavelet coefficients are selected for watermark embedding from each sub-band except the lowest frequency one. Then, each watermark bit is adaptively embedded with different strength into the selected wavelet packet coefficients based on the odd or even value after quantization. Experimental results show that the proposed method is effective for copyright verification and robust to various common attacks such as Gaussian noise, JPEG compression, and without original image as references.