ppxscal/embedding_network huggingface dataset:
An active registry for bioinformatics web services
Authors: S. Pettifer, D. Thorne, P. McDermott, T. Attwood, J. Baran, J. C. Bryne, T. Hupponen, D. Mowbray, G. Vriend
Venue: Bioinformatics (2009)

Summary: The EMBRACE Registry is a web portal that collects and monitors web services according to test scripts provided by the their administrators. Users are able to search for, rank and annotate services, enabling them to select the most appropriate working service for inclusion in their bioinformatics analysis tasks. Availability and implementation: Web site implemented with PHP, Python, MySQL and Apache, with all major browsers supported. ( www.embraceregistry.net) Contact: steve.pettifer@manchester.ac.uk
Study on the Forecast of Air Passenger Flow Based on SVM Regression Algorithm
Authors: Yan Ke-wu
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

The forecast of air passenger flow plays an important role in the management of airline, but the traditional forecast methods can't guarantee the generalization capability when they face a large-scale, multi-dimension, nonlinear and non-normal distribution time series data. To improve the forecast ability of air passenger flow, the SVM regression algorithm is introduced in this paper. By selecting appropriate parameters and kernel function, compared with the other two forecast methods, we find that the result obtained by SVM regression algorithm shows the least error among the mentioned three methods.
Spectral clustering of biological sequence data
Authors: William Pentney, Marina Meila
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

In this paper, we apply spectral techniques to clustering biological sequence data that has proved more difficult to cluster effectively. For this purpose, we have to (1) extend spectral clustering algorithms to deal with asymmetric affinities. like the alignment scores used in the comparison of biological sequences. and (2) devise a hierarchical algorithm that can handle many clusters with imbalanced sizes robustly. We present an algorithm for clustering asymmetric affinity data, and demonstrate the performance of this algorithm at recovering the higher levels of the Structural Classification of Proteins (SCOP) on a data base of highly conserved subsequences.
Service Value Networks
Authors: Benjamin Blau, Jan Kramer, Tobias Conte, Clemens van Dinther
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

The current industry-driven trend of providing flexible e-services lays the ground for the new research area ``service value networks'' (SVNs). We observe a rising number of industry-oriented publications provided by research departments of large companies such as IBM or SAP as well as the fact that more and more IS conferences offer special tracks on that issue. However, when it comes to formalizing and economically analyzing such SVNs that offer joint complex services to service customers, scientific approaches are in their infancy. We intend to fill this research gap by providing a clear understanding of service value networks by defining their characteristics, their structure, and their components. Mapping these aspects into a formalized model, we intend to establish a reference point for future work in the area of service value networks.
Computable Exchangeable Sequences Have Computable de Finetti Measures
Authors: Cameron E. Freer, Daniel M. Roy
Venue: Proceedings of the 5th Conference on Computability in Europe: Mathematical Theory and Computational Practice (2009)

We prove a uniformly computable version of de Finetti's theorem on exchangeable sequences of real random variables. In the process, we develop machinery for computably recovering a distribution from its sequence of moments, which suffices to prove the theorem in the case of (almost surely) continuous directing random measures. In the general case, we give a proof inspired by a randomized algorithm which succeeds with probability one. Finally, we show how, as a consequence of the main theorem, exchangeable stochastic processes in probabilistic functional programming languages can be rewritten as procedures that do not use mutation.
Interactive Intelligent Media Player Based on Head Motion Recognition
Authors: Wang Ruihu, Bi Hongwei, Liu Jiachen, Wu Lingguo, Fang Bin
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Over the last decade, human computer interaction has become an active research area, which releases people from inactive, inflexible communication with machine. In this paper, a human-machine interaction framework for intelligent media player controller is presented. The overall goal is to develop a video player system which can take action automatically based upon head interactive motion recognition. Combined with image processing technique and pattern recognition theories, the hair cue is used as prior information, and the symmetry along with distribution can be extracted to recognize the head moving direction, which controls the media player action individually, such as going to next or back. The experiment show that the method is easily to implemented and has pretty performance. The system could be transplanted into intelligent home appliance conveniently as well.
Bayesian binary kernel probit model for microarray based cancer classification and gene selection
Authors: Sounak Chakraborty
Venue: Computational Statistics Data Analysis (2009)

With the arrival of gene expression microarrays a new challenge has opened up for identification or classification of cancer tissues. Due to the large number of genes providing valuable information simultaneously compared to very few available tissue samples the cancer staging or classification becomes very tricky. In this paper we introduce a hierarchical Bayesian probit model for two class cancer classification. Instead of assuming a linear structure for the function that relates the gene expressions with the cancer types we only assume that the relationship is explained by an unknown function which belongs to an abstract functional space like the reproducing kernel Hilbert space. Our formulation automatically reduces the dimension of the problem from the large number of covariates or genes to a small sample size. We incorporate a Bayesian gene selection scheme with the automatic dimension reduction to adaptively select important genes and classify cancer types under an unified model. Our model is highly flexible in terms of explaining the relationship between the cancer types and gene expression measurements and picking up the differentially expressed genes. The proposed model is successfully tested on three simulated data sets and three publicly available leukemia cancer, colon cancer, and prostate cancer real life data sets.
Functional verification of power gated designs by compositional reasoning
Authors: Cindy Eisner, Amir Nahir, Karen Yorav
Venue: Formal Methods in System Design (2009)

Power gating is a technique for low power design in which whole sections of the chip are powered off when they are not needed, and powered back on when they are. Functional correctness of power gating is usually checked at the system level, where the most widely used technique is simulation using pseudo-random stimuli. This normally entails running extremely expensive ternary simulations, in order to model the memory loss that occurs as a result of a memory element being powered off. We propose instead a methodology in which we prove sequential equivalence between the power gated design and a simplified version of itself, then use the simplified version in a binary simulation. We use a compositional approach that looks for partial equivalence of each unit under a suitable set of assumptions, guaranteed by the neighboring units. The partial equivalences are then composed into total equivalence on the whole chip. Our method is applicable to any power gated design, no matter the side effects (e.g., in timing of events across the interfaces) caused by the particular implementation of power gating.
Facial Expression Recognition Based on NMF and SVM
Authors: Ying Zilu, Zhang Guoyi
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

A novel approach to facial expression recognition (FER) based on the combination of Non-negative Matrix Factorization (NMF) and Support Vector Machine (SVM) was proposed. One key step in FER is to extract expression features from the original face images. NMF is an effective approach to extract expression features because NMF decomposition makes the reconstruction of expression images in a non-subtractive way and is much similar to the process of forming unity from parts. The proposed algorithm first processes facial expression image with histogram equalization operator. Then NMF method is used for feature dimension reduction and SVM for classification. Finally, the algorithm was implemented with Matlab and experimented in Japanese female facial expression database (JAFEE database). A recognition rate of 66.19% was obtained and showed the effectiveness of the proposed algorithm
An econometric analysis of SARS and Avian Flu on international tourist arrivals to Asia
Authors: Michael McAleer, Bing-Wen Huang, Hsiao-I. Kuo, Chi-Chung Chen, Chia-Lin Chang
Venue: Environmental Modelling Software (2010)

This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu are compared directly according to the number of human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic model, respectively. Empirical results from the static fixed effect and difference transformation dynamic models are consistent, and indicate that both the short run and long run SARS effect have a more significant impact on international tourist arrivals than does Avian Flu. In addition, the effects of deaths arising from both SARS and Avian Flu suggest that SARS is more important to international tourist arrivals than is Avian Flu. Thus, while Avian Flu is here to stay, its effect is currently not as significant as that of SARS.
Ontology Evaluation through Text Classification
Authors: Yael Netzer, David Gabay, Meni Adler, Yoav Goldberg, Michael Elhadad
Venue: Advances in Web and Network Technologies, and Information Management: APWeb/WAIM 2009 International Workshops: WCMT 2009, RTBI 2009, DBIR-ENQOIR 2009, PAIS 2009, Suzhou, China, April 2-4, 2009, Revised Selected Papers (2009)

We present a new method to evaluate a search ontology, which relies on mapping ontology instances to textual documents. On the basis of this mapping, we evaluate the adequacy of ontology relations by measuring their classification potential over the textual documents. This data-driven method provides concrete feedback to ontology maintainers and a quantitative estimation of the functional adequacy of the ontology relations towards search experience improvement. We specifically evaluate whether an ontology relation can help a semantic search engine support exploratory search.We test this ontology evaluation method on an ontology in the Movies domain, that has been acquired semi-automatically from the integration of multiple semi-structured and textual data sources (e.g., IMDb and Wikipedia). We automatically construct a domain corpus from a set of movie instances by crawling the Web for movie reviews (both professional and user reviews). The 1-1 relation between textual documents (reviews) and movie instances in the ontology enables us to translate ontology relations into text classes. We verify that the text classifiers induced by key ontology relations (genre, keywords, actors) achieve high performance and exploit the properties of the learned text classifiers to provide concrete feedback on the ontology.The proposed ontology evaluation method is general and relies on the possibility to automatically align textual documents to ontology instances.
An Efficient Lightweight Shared Cache Design for Chip Multiprocessors
Authors: Jinglei Wang, Dongsheng Wang, Yibo Xue, Haixia Wang
Venue: Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies (2009)

The large working sets of commercial and scientific workloads favor a shared L2 cache design that maximizes the aggregate cache capacity and minimizes off-chip memory requests in Chip Multiprocessors (CMP). The exponential increase in the number of cores results in the commensurate increase in the memory cost of directory, restricting its scalability severely. To resolve this hurdle, a novel Lightweight Shared Cache design is proposed in this paper, which applies two small fast caches to store and manage the data and directory vectors for the blocks recently cached by L1 caches in each tile of CMP. The proposed cache scheme removes the directory vectors from L2 cache, thus decreases on-chip directory memory overhead and improves the scalability. Moreover, the proposed cache scheme brings significant reductions in terms of the L1 cache miss latencies, which lead to the improvement of program performance by 6% on average, and up to 16% at best, with 0.18% storage overhead.
Normalization Impact on SVD-Based Iris Recognition
Authors: Pavel Moravec, Petr Gajdos, Václav Snasel, Khalid Saeed
Venue: Proceedings of the 2009 International Conference on Biometrics and Kansei Engineering (2009)

In this paper, we compare the performance of singular value decomposition for the recognition of human irises based for both unmodified irises and their normalized versions.
Change Detection from Remote Sensing Imageries Using Spectral Change Vector Analysis
Authors: Xingping Wen, Xiaofeng Yang
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

Change detection using remote sensing data is the process of identifying and examining temporal, spatial and spectral changes of pixel signal. This paper detected land cover changes from two Landsat ETM+ imageries using spectral change vector analysis (CVA). CVA is a change detection technique that can determine the direction and magnitude of changes in multidimensional spectral vector. In this paper, the change magnitudes were computed by the Euclidean distance between two pair vector, and change directions were obtained by comparing the value of pair vector. The magnitude and direction image were computed and the direction of changes were analyzed. Finally, the change image in false color was output. CVA is an effective change detection technique. The accuracy evaluation and direction of change vector analysis need further study.
ViewpointA "smart" cyberinfrastructure for research
Authors: Savas Parastatidis, Evelyne Viegas, Tony Hey
Venue: Communications of the ACM (2009)

A view of semantic computing and its role in research.
ILK: machine learning of semantic relations with shallow features and almost no data
Authors: Iris Hendrickx, Roser Morante, Caroline Sporleder, Antal van den Bosch
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

This paper summarizes our approach to the Semeval 2007 shared task on "Classification of Semantic Relations between Nominals". Our overall strategy is to develop machine-learning classifiers making use of a few easily computable and effective features, selected independently for each classifier in wrapper experiments. We train two types of classifiers for each of the seven relations: with and without WordNet information.
Training for Task Specific Keypoint Detection
Authors: Christoph Strecha, Albrecht Lindner, Karim Ali, Pascal Fua
Venue: Proceedings of the 31st DAGM Symposium on Pattern Recognition (2009)

In this paper, we show that a better performance can be achieved by training a keypoint detector to only find those points that are suitable to the needs of the given task. We demonstrate our approach in an urban environment, where the keypoint detector should focus on stable man-made structures and ignore objects that undergo natural changes such as vegetation and clouds. We use WaldBoost learning with task specific training samples in order to train a keypoint detector with this capability. We show that our aproach generalizes to a broad class of problems where the task is known beforehand.
What is <u>at stake</u>: a case study of Russian expressions starting with a preposition
Authors: Serge Sharoff
Venue: Proceedings of the Workshop on Multiword Expressions: Integrating Processing (2004)

The paper describes an experiment in detecting a specific type of multiword expressions in Russian, namely expressions starting with a preposition. This covers not only prepositional phrases proper, but also fixed syntactic constructions like v techenie ('in the course of'). First, we collect lists of such constructions in a corpus of 50 mln words using a simple mechanism that combines statistical methods with knowledge about the structure of Russian prepositional phrases. Then we analyse the results of this data collection and estimate the efficiency of the collected list for the resolution of morphosyntactic and semantic ambiguity in a corpus.
Modelling and recognition of the linguistic components in American Sign Language
Authors: Liya Ding, Aleix M. Martinez
Venue: Image and Vision Computing (2009)

The manual signs in sign languages are generated and interpreted using three basic building blocks: handshape, motion, and place of articulation. When combined, these three components (together with palm orientation) uniquely determine the meaning of the manual sign. This means that the use of pattern recognition techniques that only employ a subset of these components is inappropriate for interpreting the sign or to build automatic recognizers of the language. In this paper, we define an algorithm to model these three basic components form a single video sequence of two-dimensional pictures of a sign. Recognition of these three components are then combined to determine the class of the signs in the videos. Experiments are performed on a database of (isolated) American Sign Language (ASL) signs. The results demonstrate that, using semi-automatic detection, all three components can be reliably recovered from two-dimensional video sequences, allowing for an accurate representation and recognition of the signs.
Research on Spatial Data Emergency Coordinating and Sharing System Construction
Authors: Cheng Dong, Jia Chang Chen
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

The importance of spatial data application has been fully displayed in Wenchuan Earthquake relief activities. Spatial data has been the basic factor of various relief activities. Wenchuan Earthquake relief process also uncovered many problems on the spatial data emergency application of our country. The exertion of spatial data has been greatly controlled by the coordination capability of each department during data collecting and sharing processes. So, state must establish the spatial data emergency coordinating and sharing system (SDECSS) according to real requirements and social situations. This paper carried out research on the system’s necessity, overall plan, and department selection etc.
Parameter Optimization of Multi-mode Vibration Control System
Authors: Xiaobing Luo, Rujian Ma, Guixi Li, Dong Zhao
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

The parameter optimization of the multiple tuned mass damper system are studied in this paper by establishing the dynamic model of the multi-mode control of the multi-degree-of-freedom structure and vibration control system. The transfer functions and dynamic magnification factors of the multi-mode control of the multi-degrees-of-freedom structure and vibration control system are derived first. The parameter optimization study of the vibration control system is then performed, where the minimum of the dynamic magnification factor is used as the optimal objective. Furthermore, the optimal vibration control effects of single mode control and multi-mode control are studied. The application examples are finally given and indicated that this method has the characteristics of better suitability and high accurate.
User Feedback for Improving Question Categorization in Web-Based Question Answering Systems
Authors: Wanpeng Song, Liu Wenyin, Naijie Gu, Xiaojun Quan
Venue: Advances in Web and Network Technologies, and Information Management: APWeb/WAIM 2009 International Workshops: WCMT 2009, RTBI 2009, DBIR-ENQOIR 2009, PAIS 2009, Suzhou, China, April 2-4, 2009, Revised Selected Papers (2009)

Question categorization, which automatically suggests a few categories to host a user's question, is a useful technique in Web-based question answering systems. In this paper, we propose a question categorization method which makes use of user feedback to the system's automatic suggestions to improve question categorization. We initialize the categorization model by training a set of accumulated questions. When a user asks a question, the system automatically suggests a few categories for the question using the current categorization model. The user can then select one of these suggestions or another category and such feedback information is used to revise the categorization model. The revised model is used to categorize new questions. Experimental results show that our method is effective to take the advantages of both positive and negative feedback to improve the precision of question categorization but finish the revision of the categorization model in real time.
Layered Intelligence for Agent-based Crowd Simulation
Authors: Bikramjit Banerjee, Ahmed Abukmail, Landon Kraemer
Venue: Simulation (2009)

We adapt a scalable layered intelligence technique from the game industry, for agent-based crowd simulation. We extend this approach for planned movements, pursuance of assignable goals, and avoidance of dynamically introduced obstacles/threats as well as congestions, while keeping the system scalable with the number of agents. We demonstrate the various behaviors in hall-evacuation scenarios, and experimentally establish the scalability of the frame rates with increasing numbers of agents.
From Molecules to Medicines: Structure of Biological Macromolecules and Its Relevance in Combating New Diseases and Bioterrorism, 1st edition
Authors: Joel L. Sussman, Joel L. Sussman, Paola Spadon
Venue: Nato Science For Peace And Security Series A Chemistry And Biology (2009)

The synergism played by crystallography and drug discovery is the central focus of this volume which comprises papers presented at the 40th Erice Course held from 28 May to 8 June 2008. A key theme throughout the book is the dependence of modern structural science on multiple experimental and computational techniques, and it is the development of these techniques and their integration that will take us forward in the future.
Holonic Modelling of Large Scale Geographic Environments
Authors: Mehdi Mekni, Bernard Moulin
Venue: Proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2009)

In this paper, we propose a novel approach to model Virtual Geographic Environments (VGE) which uses the holonic approach as a computational geographic methodology and holarchy as organizational principle. Our approach allows to automatically build VGE using data provided by Geographic Information Systems (GIS) and enables an explicit representation of the geographic environment for Situated Multi-Agent Systems (SMAS) in which agents are situated and with which they interact. In order to take into account geometric, topologic, and semantic characteristics of the geographic environment, we propose the use of the holonic approach to build the environment holarchy. We illustrate our holonic model using two different environments: an urban environment and a natural environment.