ppxscal/embedding_network huggingface dataset:
Discovering regularities in biosequences: Challenges and applications
Authors: C. H. Makris, K. Perdikuri, A. Tsakalidis
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

Computational methods on molecular sequence data are at the heart of computational molecular biology. Identification of known or unknown DNA and RNA motifs or regions involved in various biological processes such as initiation of transcription, gene expression and translation, or the discovery of various types of repeats are some of the applications of major concern. An accurate identification and localization of such elements will allow biologists to perform deeper studies of the structure, function and evolution of genomes. This requires the development of faster and more complex mathematical models and computer algorithms. In this work we discuss current techniques to cope with string problems in molecular sequence data. We focus on Weighted Sequences and Sequences with "don't care characters", explaining the open problems and their relevance to biological applications.
Medical Image Segmentation Based on the Bayesian Level Set Method
Authors: Yao-Tien Chen, Din-Chang Tseng
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

A level set method based on the Bayesian risk is proposed for medical image segmentation. At first, the image segmentation is formulated as a classification of pixels. Then the Bayesian risk is formed by false-positive and false-negative fractions in a hypothesis test. Through minimizing the average risk of decision in favor of the hypotheses, the level set evolution functional is deduced for finding the boundaries of targets. To prevent the propagating curves from generating excessively irregular shapes and lots of small regions, curvature and gradient of edges in the image are integrated into the functional. Finally, the Euler-Lagrange formula is used to find the iterative level set equation from the derived functional. Comparing with other level-set methods, the proposed approach relies on the optimum decision of pixel classification; thus the approach has more reliability in theory and practice. Experiments show that the proposed approach can accurately extract the complicated shape of targets and is robust for various types of images including high-noisy and low-contrast images, CT, MRI, and ultrasound images; moreover, the algorithm is extendable for multiphase segmentation.
Coordination Mechanism for optimized provision of services in an area
Authors: Yuki Mori, Fumiko Harada, Hiromitsu Shimakawa
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

We are aiming at achievements of the Unconscious Computing to provide users with ubiquitous services even if they are not conscious of ubiquitous computer environments. In the Unconscious Computing, a user's cellular phone recognizes the actions that the user should do. A server is installed in an area to know the number of resources such as buy-ticket places or ticket reservation counter and to manage the their usage status. When the user enters an area, his cellular phone provides the user with services which let him execute actions to require the resources through the server. However, it is difficult to provide services to all users if they are requesting services for the same resources from the same area. To solve this problem, this paper proposes the Action Arbitration Function to arbitrate the competition for resources. The Action Arbitration Function integrates the action schedules of the users competing for a resource, reschedules the actions, and provides services to a user who has a tight action in consideration of their future actions.
MetaVex: Regulation Drafting Meets the Semantic Web
Authors: Saskia Ven, Rinke Hoekstra, Radboud Winkels, Emile Maat, Ádám Kollár
Venue: Computable Models of the Law: Languages, Dialogues, Games, Ontologies (2008)

Currently almost all legislative bodies throughout Europe use general purpose word-processing software for the drafting of legal documents. These regular word processors do not provide specific support for legislative drafters and parliamentarians to facilitate the legislative process. Furthermore, they do not natively support metadata on regulations. This paper describes how the MetaLex regulation-drafting environment (MetaVex) aims to meet such requirements.
Generalized Non-deterministic Matrices and (n,k)-ary Quantifiers
Authors: Arnon Avron, Anna Zamansky
Venue: Proceedings of the international symposium on Logical Foundations of Computer Science (2007)

An (n,k)-ary quantifier is a generalized logical connective, binding k variables and connecting n formulas. Canonical Gentzen-type systems with (n,k)-ary quantifiers are systems which in addition to the standard axioms and structural rules have only logical rules in which exactly one occurrence of an (n,k)-ary quantifier is introduced. The semantics of such systems for the case of k ¿ {0,1} are provided in [16] using two-valued non-deterministic matrices (2Nmatrices). A constructive syntactic coherence criterion for the existence of a 2Nmatrix for which a canonical system is strongly sound and complete, is formulated there. In this paper we extend these results from the case of k ¿ {0,1} to the general case of k ¿ 0. We show that the interpretation of quantifiers in the framework of Nmatrices is not sufficient for the case of k > 1 and introduce generalized Nmatrices which allow for a more complex treatment of quantifiers. Then we show that (i) a canonical calculus G is coherent iff there is a 2GNmatrix, for which G is strongly sound and complete, and (ii) any coherent canonical calculus admits cut-elimination.
MoViSys --- A Visualization System for Geo-Referenced Information on Mobile Devices
Authors: Maria Beatriz Carmo, Ana Paula Afonso, Paulo Pombinho De Matos, Ana Vaz
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

Visualization of geo-referenced information on mobile devices can be useful in diverse areas. These applications require a user-friendly interface to enable querying the data interactively and the generation of intelligible images. Moreover, they must deal with the limitations of mobile devices, such as small screen size, and the context of mobility. This paper describes MoViSys, a visualization system for geo-referenced data, organized in several categories with multiple attributes, on mobile devices. This system explores filtering mechanisms to present the result of interactive queries specified through an adaptive interface.
Real-Time Routing in Wireless Sensor Networks
Authors: Adel Ali Ahmed, Liza Abdul Latiff, M. A. Sarijari, Norsheila Fisal
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

In Wireless Sensor Networks (WSNs), sensors gather information about the physical world and base station makes appropriate decision upon the environment. This technology enables users to effectively sense and monitor from a distance. WSN are slated to become very popular in the near future. It allows video/audio streaming to be transferred between sensor nodes in real-time. WSN can use real-time forwarding which means messages in the network are delivered according to their end-to-end deadlines (packet lifetime). This paper proposes a novel real-time routing protocol based on link quality, packet velocity over one-hop and remaining power in the sensor devices. The proposed routing has been successfully studied and verified through simulation and real test bed implementation. The results in this paper show that the proposed routing protocol has efficient power consumption, high packet delivery ratio and minimum control packet overhead in WSNs.
Bayesian Substructure Learning - Approximate Learning of Very Large Network Structures
Authors: Andreas Nägele, Mathäus Dejori, Martin Stetter
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

In recent years, Bayesian networks became a popular framework to estimate the dependency structure of a set of variables. However, due to the NP-hardness of structure learning, this is a challenging task and typical state-of-the art algorithms fail to learn in domains with several thousands of variables. In this paper we introduce a novel algorithm, called substructure learning, that reduces the complexity of learning large networks by splitting this task into several small subtasks. Instead of learning one complete network, we estimate the network structure iteratively by learning small subnetworks. Results from several benchmark cases show that substructure learning efficiently reconstructs the network structure in large domains with high accuracy.
Application of fuzzy subtractive clustering for enzymes classification
Authors: Gita Sastria, Choong-Yeun Liong, Ishak Hashim
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

Enzymes are a subclass of proteins that are specialized in catalytic activity. Protein classification problem is a difficult task because of the complexity in function and structural characteristics. This brings the necessity of computer-based methods like machine learning, artificial intelligence and data mining to solving the protein classification problems. The goal of this study is to propose the application of Fuzzy Subtractive Clustering (FSC) technique to classify the function of an enzyme by analyzing its structural class similarity to families of enzymes. A codification scheme was implemented to convert the primary structure of enzymes into a real-valued vector. To evaluate our study, the dataset obtained from Protein Data Bank (PDB) family database are used as the experimental datasets. The computational results have shown that FSC technique gives a better overall success prediction rate of 84.53% on average in comparison to previously published results.
Itanium 2 Processor 6M: Higher Frequency and Larger L3 Cache
Authors: Stefan Rusu, Harry Muljono, Brian Cherkauer
Venue: IEEE Micro (2004)

In designing the next generation of the Itanium 2 processor, Intel doubled the on-die, level-three cache to 6 Mbytes and increased frequency by 50 percent compared to the previous generation. Another goal was to keep the power dissipation of the new design within the same envelope as its predecessor.
Mathematical tool of discrete dynamic modeling of complex systems in control loop
Authors: Armen Bagdasaryan
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

In this paper we present a method of discrete modeling and analysis of multi-level dynamics of complex large-scale hierarchical dynamic systems subject to external dynamic control mechanism. In a model each state describes parallel dynamics and simultaneous trends of changes in system parameters. The essence of the approach is in analysis of system state dynamics while it is in the control loop.
IT governance and performance measurement: research study on Croatian companies
Authors: Mario Spremic, Zlatan Žmirak, Krunoslav Kraljevic
Venue: Proceedings of the 7th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (2008)

As the organizations are becoming increasingly dependent upon IT in order to achieve their corporate objectives and meet their business needs, the necessity for implementing widely applicable IT best practices standards and methodologies, offering high quality IT services is evident. IT profession has been in search for solid standards and performance measurement frameworks for decades, but it seems that by the 1990's such efforts had dramatically improved. One of the reasons for such tendencies may be in changing role of IT performance metrics over years. While in 1980's the focus of IT performance metrics was solely on technical efficiency, in 1990's process efficiency was attached, these efforts nowadays converge to comprehensive concept of value added IT-related business benefits. IT Governance issues are not only any more marginal or 'technical' problems and become more and more a 'business problem'. Therefore, in this paper emerging issues in IT Governance are discussed and the necessity for IT Audit and Performance Measurement initiatives stressed. Contemporary issues in measuring IT performance are associated with engaging in periodical audits of IT and their contribution to the business. The concept of IT Audit, as a systematically 'tool' for measuring IT performance, is shown and explained in further details, together with the methodologies used for their implementation (CobiT, ITIL, ISO 27001). Finally, on the sample of selected Croatian large companies, research question about the level of IT maturity used in businesses is answered. Vast majority of IT Governance components and issues are argued in the research.
Mobile Java RMI support over heterogeneous wireless networks: A case study
Authors: Chung-Kai Chen, Cheng-Wei Chen, Chien-Tan Ko, Jenq-Kuen Lee, Jyh-Cheng Chen
Venue: Journal of Parallel and Distributed Computing (2008)

Distributed object-oriented platforms are increasingly important in wireless environments to provide frameworks for collaborative computation and for managing a large pool of distributed resources. One of the important layers for implementing distributed computing in such environments is via remoting mechanisms. For example, Java uses Remote Method Invocation (RMI) for handling distributed controls. In this paper, we investigate the support for this important layer on wireless environments and address the issues to support Java RMI over heterogeneous wireless environments. We present a case study for supporting Java RMI in Bluetooth, GPRS, and WLAN environments, which represents an important middleware for component communications. The Bluetooth layer is supported by incorporating a set of protocol stack layers for Bluetooth, known as JavaBT that has been developed by us, and by supporting an L2CAP layer with sockets to support Java RMI sockets. RMI over GPRS/WLAN is achieved by RMI implementation over IP layer. Our support for the roaming of Java RMI over heterogeneous wireless networks is based on the concept of direct connection, which avoids the problems caused by forwarding. The difficulty of this strategy is how to handle the existing connection when the mobile node moves to another location so as to avoid interruption of the high-level applications. We solve this problem in Java RMI by the support of dynamic addresses and dynamic sockets. We also propose algorithms to handle the handoff process. In addition, methods for connect-loss detection and data-integrity maintenance in dealing with roaming scenarios are also presented. Java Grande benchmarks are used to demonstrate that our RMI implementations over GPRS, WLAN, and Bluetooth networks are effective in supporting parallel and distributed control of Java layers in heterogeneous wireless environments.
Topic 5 Parallel and Distributed Databases
Authors: Marta Patiño-Martinez, Genoveva Vargas-Solar, Elena Baralis, Bettina Kemme
Venue: Proceedings of the 13th European international conference on Parallel Processing (2007)

Advances in data exploitation (access, query, retrieval, analysis, mining) are inherent to current and future information systems. Today, accessing great volumes of information is reality; tomorrow data intensive management systems will enable huge user communities to transparently access multiple pre-existing autonomous, distributed and heterogeneous resources (data, documents, services). Existing data management solutions do not provide efficient techniques for exploiting and mining tera-datasets available in clusters, peer to peer and grid architectures. Parallel and distributed databases are a key element for achieving scalable, efficient systems that will both cost-effectively manage and extract knowledge from huge amounts of highly distributed and heterogeneous digital data repositories.
Generation reliability assessment in power pool market using MCS and intelligent systems
Authors: H. Haroonabadi, M.-R. Haghifam
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In this paper, generation reliability is considered, and a method for its assessment using intelligent systems is proposed. Also, because of power market and generators' forced outages stochastic behavior, Monte Carlo Simulation is used for reliability evaluation. Generation reliability, merely focuses on interaction between generation complex and load. Therefore, in this research, based on market type and its concentration, reserve margin, and various future times, a Neuro-Fuzzy system is proposed for evaluation of generation reliability which is valid and usable for all kinds of power pool markets. Finally, the proposed method is assessed on IEEE-Reliability Test System; and generation reliability indices of various markets are evaluated with different parameters.
Integrated modelling of sonic vibration and macroscopic object movement: an example of an interactive ball game
Authors: Matthias Rath, Sascha Bienert
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

Digital artifacts based on physical metaphors strongly benefit from dynamic, realtime reactive sound feedback. Making use of one integral physical model and digital implementation simultaneously for both, macroscopic, visual object behaviour and sonic feedback allows to realise scenarios not achievable in a conventional approach where sound is triggered or controlled in a one-way fashion from a macroscopic simulation. By careful consideration of possible simplifications such an integrated approach may be feasible in realtime implementation and can allow to reach higher levels of synchronicity and sensory integration.
Independent component analysis for data mining
Authors: Mark J. Embrechts
Venue:  (2007)

Data mining is the science of extracting novel and potentially useful information from large data sets [68]. An important problem in data mining is to represent multivariate data and extract useful features from the data. For simplicity, the observed data is usually assumed to be a linear mixture of some latent variables. Well-known linear transformation methods include Principal Component Analysis (PCA), Partial Least Squares (PLS), Canonical Correlation Analysis (CCA), and Factor Analysis (FA). These methods find uncorrelated components from the data. Independent Component Analysis (ICA) is a recently developed method for finding a linear transformation in which the extracted components are mutually independent, which is a stronger condition than uncorrelated. This thesis focuses on algorithms and applications of ICA for data mining.Several different ICA algorithms have been published to solve the Blind Source Separation (BSS) problem based on different principles, which measure statistical independence in different ways. In this research, an extended ICA algorithm is proposed within the framework of information-theoretic learning. The performance of this algorithm and existing ICA algorithms is studied. The close connection between PCA and ICA is investigated within the information-theoretic framework learning as well. It is shown that ICA becomes PCA when the higher-order terms in the Gram-Charlier series are dropped. ICA is introduced as a general data preprocessing tool. And a pseudo-inverse ICA filtering algorithm is introduced for data cleansing. The ICA filtering algorithm is able to filter out any components including noise from the data. This helps improve the quality of the data, leading to improved results when applying data mining techniques to the cleaned data. In addition to being used in the derivation of the ICA algorithms, the information theory is also introduced for outlier detection problems.ICA is applied to three applications: cleaning the terahertz spectra of explosives, denoising the terahertz images of explosives, and separating the terahertz spectrum of water vapor.
Passive Monitoring of DNS Anomalies
Authors: Bojan Zdrnja, Nevil Brownlee, Duane Wessels
Venue: Proceedings of the 4th international conference on Detection of Intrusions and Malware, and Vulnerability Assessment (2007)

We collected DNS responses at the University of Auckland Internet gateway in an SQL database, and analyzed them to detect unusual behaviour. Our DNS response data have included typo squatter domains, fast flux domains and domains being (ab)used by spammers. We observe that current attempts to reduce spam have greatly increased the number of A records being resolved. We also observe that the data locality of DNS requests diminishes because of domains advertised in spam.
Binary Trees and (Maximal) Order Types
Authors: Gyesik Lee
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

Concerning the set of rooted binary trees, one shows that Higman's Lemma and Dershowitz's recursive path ordering can be used for the decision of its maximal order type according to the homeomorphic embedding relation as well as of the order type according to its canonical linearization, well-known in proof theory as the Feferman-Sch&uuml;tte notation system without terms for addition. This will be done by showing that the ordinal &omega; n + 1 can be found as the (maximal) order type of a set in a cumulative hierarchy of sets of rooted binary trees. 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
Quantum-Inspired Evolutionary Algorithm for Transportation Network Design Optimization
Authors: Xinping Yan, Nengchao Lv, Zhenglin Liu, Kun Xu
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

Transportation network design problem deals with how to add or improve some edges on an existing transportation network to improve traffic condition. In this study a bi-level programming model was proposed to optimize the strategy of transportation network capacity improvement in the constraint of budget. The upper level problem aims to minimize the total travel time of all transportation travelers, while the lower level model is users' equilibrium transportation assignment model. A quantum-inspired evolutionary algorithm was employed to solve the problem. The result of numerical experiment indicated that the proposed model can reduce total travel time by searching optimal solution and the QEA is more efficient than other heuristic algorithm.