ppxscal/embedding_network huggingface dataset:
Scoring and summarising gene product clusters using the Gene Ontology
Authors: Spiridon C. Denaxas, Christos Tjortjis
Venue: International Journal of Data Mining and Bioinformatics (2008)

We propose an approach for quantifying the biological relatedness between gene products, based on their properties, and measure their similarities using exclusively statistical NLP techniques and Gene Ontology (GO) annotations. We also present a novel similarity figure of merit, based on the vector space model, which assesses gene expression analysis results and scores gene product clusters' biological coherency, making sole use of their annotation terms and textual descriptions. We define query profiles which rapidly detect a gene product cluster's dominant biological properties. Experimental results validate our approach, and illustrate a strong correlation between our coherency score and gene expression patterns.
A note on the transitivity of parthood
Authors: Achille C. Varzi
Venue: Applied Ontology (2006)

That parthood is a transitive relation is among the most basic principles of classical mereology. Alas, it is also very controversial. In a recent paper, Ingvar Johansson has put forward a novel diagnosis of the problem, along with a corresponding solution. The diagnosis is on the right track, I argue, but the solution is misleading. And once the pieces are properly put together, we end up with a reinforcement of the standard defense of transitivity on behalf of classical mereology.
Learning to Shoot Goals Analysing the Learning Process and the Resulting Policies
Authors: Markus Geipel, Michael Beetz
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

Reinforcement learning is a very general unsupervised learning mechanism. Due to its generality reinforcement learning does not scale very well for tasks that involve inferring subtasks. In particular when the subtasks are dynamically changing and the environment is adversarial. One of the most challenging reinforcement learning tasks so far has been the 3 to 2 keepaway task in the RoboCup simulation league. In this paper we apply reinforcement learning to a even more challenging task: attacking the opponents goal. The main contribution of this paper is the empirical analysis of a portfolio of mechanisms for scaling reinforcement learning towards learning attack policies in simulated robot soccer.
The Garnata Information Retrieval System at INEX'07
Authors: Luis M. Campos, Juan M. Fernández-Luna, Juan F. Huete, Carlos Martín-Dancausa, Alfonso E. Romero
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

This paper exposes the results of our participation at INEX'07 in the AdHoc track and the comparison of these results with respect to the ones obtained last year. Three runs were submitted to each of the Focused, Relevant In Context and Best In Context tasks, all of them obtained with Garnata, our Information Retrieval System for structured documents. As in the past year, we use a model based on Influence Diagrams, the CID model. The result of our participation has been better than the last year and we have reached an acceptable position in the ranking for the three tasks. In the paper we describe the model, the system and we show the differences between our systems at INEX'06 and INEX'07, which make possible to get a better performance.
Heavy Tails and Web Models
Authors: Prabhakar Raghavan
Venue: Proceedings of the 2nd international conference on Scalable Uncertainty Management (2008)

The literature is rich with (re)discoveries of power law phenomena; this is especially true of observations of link and traffic behavior on the Web. We survey the origins of these phenomena and several (yet incomplete) attempts to model them. We then present a number of open problems in Web research arising from these observations.
A User Interface for the User-Centred Knowledge Model, t-UCK
Authors: Anne Håkansson
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

This paper presents a user interface to the User-Centred Knowledge Model (t-UCK). T-UCK is a knowledge modelling tool for designing knowledge-intensive systems. The model centres round the various users, i.e., both the design users and the end users, and facilitates the use of a conceptual model for handling different types of knowledge, the reasoning strategy and other functionality. For the design users, the conceptual model is presented through a modelling view of the contents used for developing the system. For the end users, the conceptual model has a parallel consulting view used for sessions with the system. Both these views are directly modelled into the system through a graphical modelling language, the Unified Modelling Language (UML). UML is a general-purpose modelling language, which in a modified form it can be used for development of knowledge-based systems.
Response of magnetostrictive smart structures to sinusoidal and step force inputs
Authors: Sultan Aljahdali, Syed J. Hyder
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

Constitutive equations of magnetostrictive smart materials involving mechanical and magnetic fields are presented via Hamilton's principle. Finite element equations are used to solve the equations of motion subjected to different force inputs. Magnetostrictive (CoFe$_{2}$O$_{4}$) layers mounted on the root of cantilever beam is considered as the case study to obtain the displacement and magnetic response both in the X and Y directions when subjected to sinusoidal and step force inputs. Fast Fourier Transformation (FFT) technique is also employed to obtain the Power Spectral Density (PSD) of displacement and magnetic responses in both X and Y directions.
Characterizing mobile ad hoc networks -: the maniac challenge experiment
Authors: Vivek Srivastava, Amr B. Hilal, Michael S. Thompson, Jawwad N. Chattha, Allen B. MacKenzie, Luiz A. DaSilva
Venue: Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization (2008)

This paper reports data collected during the first Mobile Ad-hoc Network Interoperability And Cooperation (MANIAC) Challenge, a multi-institution competition that allows us to study issues of interoperability and cooperation in mobile ad hoc networks (MANETs). We characterize network topology and routing. The former includes network connectivity and diameter, node degree distribution, clustering, and frequency of topology changes. The latter includes route length distribution, route asymmetry, frequency of route changes, and packet delivery ratio. Results show a high degree of topology and route changes, even when mobility is low, and a prevalence of asymmetric routes, both of which contradict assumptions commonly made in MANET simulation studies. Our data sets will be made publicly available for use by other researchers.
Assertions Signcryption Scheme in Decentralized Autonomous Trust Environments
Authors: Mingwu Zhang, Bo Yang, Shenglin Zhu, Wenzheng Zhang
Venue: Proceedings of the 5th international conference on Autonomic and Trusted Computing (2008)

Trust management is a crucial approach to authenticate user and protect resource in distributed systems. Trust between two unknown parties in different autonomous domain is established based on the parties properties, by which are proven their qualifications through the disclosure of appropriate credentials. Assertion, described as well-defined uniformly semantic structure entities such as credentials, policies and requests, is encrypted by issuer or authority's public key. In this paper, we propose an efficient assertion security protect model based on signcryption scheme for multiple autonomous domain managers and privacy key generators(PKGs). We proved its security including confidentiality, unforgeability, public verifiability, and ciphertext anonymity under the DBDH assumption in the random oracle model, where the proposed scheme has comparable advantage in security and efficiency to other previous ID-based signcryption schemes in multiple PKGs.
On the use of liquid bridges as tensiometers
Authors: M. G. Cabezas, J. M. Montanero
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

The measurement of the surface tension associated with the interface between two immiscible liquids requires the use of non-trivial experimental procedures. The Axisymmetric Drop Shape Analysis (ADSA) method has been used by several laboratories because it provides good results over a wide range of situations. In the ADSA method, the theoretical prediction for a drop equilibrium shape is fitted to experimental contours to find the surface tension value. Based on this idea, in the present paper the advantages of using liquid bridges instead of drops are discussed. The sensitivity of both the drop and the liquid bridge equilibrium shapes to the surface tension value is studied from the numerical solution of the Young-Laplace equation. The results show that the use of liquid bridges could lead to better results, especially if non-axisymmetric configurations are considered. The optimal values of the experimental parameters are found, and a numerical algorithm developed to calculate the surface tension value from a liquid bridge photograph is described.
An Approach to Evaluate Data Trustworthiness Based on Data Provenance
Authors: Chenyun Dai, Dan Lin, Elisa Bertino, Murat Kantarcioglu
Venue: Proceedings of the 5th VLDB workshop on Secure Data Management (2008)

Today, with the advances of information technology, individual people and organizations can obtain and process data from different sources. It is critical to ensure data integrity so that effective decisions can be made based on these data. An important component of any solution for assessing data integrity is represented by techniques and tools to evaluate the trustworthiness of data provenance. However, few efforts have been devoted to investigate approaches for assessing how trusted the data are, based in turn on an assessment of the data sources and intermediaries. To bridge this gap, we propose a data provenance trust model which takes into account various factors that may affect the trustworthiness and, based on these factors, assigns trust scores to both data and data providers. Such trust scores represent key information based on which data users may decide whether to use the data and for what purposes.
Static Specification Mining Using Automata-Based Abstractions
Authors: Sharon Shoham, Eran Yahav, Stephen J. Fink, Marco Pistoia
Venue: IEEE Transactions on Software Engineering (2008)

We present a novel approach to client-side mining of temporal API specifications based on static analysis. Specifically, we present an interprocedural analysis over a combined domain that abstracts both aliasing and event sequences for individual objects. The analysis uses a new family of automata-based abstractions to represent unbounded event sequences, designed to disambiguate distinct usage patterns and merge similar usage patterns. Additionally, our approach includes an algorithm that summarizes abstract traces based on automata clusters, and effectively rules out spurious behaviors. We show experimental results mining specifications from a number of Java clients and APIs. The results indicate that effective static analysis for client-side mining requires fairly precise treatment of aliasing and abstract event sequences. Based on the results, we conclude that static client-side specification mining shows promise as a complement or alternative to dynamic approaches.
Multi-temporal Remotely Sensed Data Processing System
Authors: Zijun Wang, Shengbo Chen, Lingjun Zhao, Xuqing Zhang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Remote sensing provides huge multi-temporal data for earth surface, which has not been used completely. In the study, based on Visual C++ and Geographic Information System (GIS) platform, a multi-temporal data processing system using Grey Model (GM) is developed. By the interactive system, some functions, such as data input/output, visualization, simulation, prediction, data transformation, comparison, and analysis, are carried out. Specifically, a Generalization GM (GGM), an extension of GM, is applied to process unequal time interval data. The procedure of “line-basic line-line” is also proposed to analyze the raster images, where every row or column of the image is taken as one basic line, a minimal unit of this system. With the help of GIS, the vector data can be processed together with raster data. At last, the system we developed is applied successfully to urban growth prediction by multi-temporal remotely sensed data.
Community-Based Load Balancing for Massively Multi-Agent Systems
Authors: Naoki Miyata, Toru Ishida
Venue: Massively Multi-Agent Technology: AAMAS Workshops, MMAS 2006, LSMAS 2006, and CCMMS 2007 Hakodate, Japan, May 9, 2006 Honolulu, HI, USA, May 15, 2007 Selected and Revised Papers (2008)

Recently, large-scale distributed multiagent systems consisting of one million of agents have been developed. When agents are distributed among multiple servers, both the computational and interaction cost of servers must be considered when optimizing the performance of the entire system. Multiagent systems reflect the structure of social communities and artificial networks such as the Internet. Since the networks possess characteristics common to the `small world' phenomenon, networks of agents on the systems can be considered as small worlds. In that case, communities, which are the sets of agents that frequently interact with each other, exist in the network. Most previous works evaluate agents one by one to select the most appropriate agent to be moved to a different server. If the networks of agents are highly clustered, previous works divide the communities when moving agents. Since agents in the same community often interact with each other, this division of communities increases the interaction cost among servers. We propose community-based load balancing (CLB), which evaluates the communities to select the most appropriate set of agents to be moved. We conducted simulations to evaluate our proposed method according to the network of agents. Our simulations show that when the clustering coefficient is close to 1.0, the interaction cost with CLB can be approximately 30% lower than that with previous works.
An Incremental and Modular Technique for Checking LTL\X Properties of Petri Nets
Authors: Kais Klai, Laure Petrucci, Michel Reniers
Venue: Proceedings of the 27th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems (2007)

Model-checking is a powerful and widespread technique for the verification of finite state concurrent systems. However, the main hindrance for wider application of this technique is the well-known state explosion problem. Modular verification is a promising natural approach to tackle this problem. It is based on the "divide and conquer" principle and aims at deducing the properties of the system from those of its components analysed in isolation. Unfortunately, several issues make the use of modular verification techniques difficult in practice. First, deciding how to partition the system into components is not trivial and can have a significant impact on the resources needed for verification. Second, when model-checking a component in isolation, how should the environment of this component be described? In this paper, we address these problems in the framework of model-checking LTL¿X action-based properties on Petri nets. We propose an incremental and modular verification approach where the system model is partitioned according to the actions occurring in the property to be verified and where the environment of a component is taken into account using the linear place invariants of the system.
Hardware Acceleration of an Immune Network Inspired Evolutionary Algorithm for Medical Diagnosis
Authors: Stephen L. Smith, Andrew Greensted, Jon Timmis
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

This paper proposes the hardware implementation of a novel evolutionary algorithm inspired by protein/substrate binding exploited in artificial immune networks. The immune network inspired evolutionary algorithm has been developed in direct response to an application in clinical neurology, the diagnosis of Parkinson's Disease, but is now being considered for other more demanding applications where real-time processing of data is required. The inspiration for the algorithm and its proposed implementation in hardware is presented. The effectiveness of the approach is shown by results obtained from a software implementation.
Prototype Selection Via Prototype Relevance
Authors: J. Arturo Olvera-López, J. Ariel Carrasco-Ochoa, J. Fco. Martínez-Trinidad
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

In Pattern recognition, the supervised classifiers use a training set T for classifying new prototypes. In practice, not all information in T is useful for classification therefore it is necessary to discard irrelevant prototypes from T. This process is known as prototype selection, which is an important task for classifiers since through this process the time in the training and/or classification stages could be reduced. Several prototype selection methods have been proposed following the Nearest Neighbor (NN) rule; in this work, we propose a new prototype selection method based on the prototype relevance and border prototypes, which is faster (over large datasets) than the other tested prototype selection methods. We report experimental results showing the effectiveness of our method and compare accuracy and runtimes against other prototype selection methods.
Mesh Signatures
Authors: Xavier Boyen
Venue: Proceedings of the 26th annual international conference on Advances in Cryptology (2007)

We define the mesh signature primitive as an anonymous signature similar in spirit to ring signatures, but with a much richer language for expressing signer ambiguity. The language can represent complex access structures, and in particular allows individual signature components to be replaced with complete certificate chains. Because withholding one's public key from view is no longer a shield against being named as a possible cosignatory, mesh signatures may be used as a ring signature with compulsory enrollment.We give an efficient construction based on bilinear maps in the common random string model. Our signatures have linear size, achieve everlasting perfect anonymity, and reduce to very efficient ring signatures without random oracles as a special case. We prove non-repudiation from a mild extension of the SDH assumption, which we introduce and justify meticulously.
Quick Training Algorithm for Extra Reduced Size Lattice-Ladder Multilayer Perceptrons
Authors: Dalius Navakauskas
Venue: Informatica (2003)

A quick gradient training algorithm for a specific neural network structure called an extra reduced size lattice-ladder multilayer perceptron is introduced. Presented derivation of the algorithm utilizes recently found by author simplest way of exact computation of gradients for rotation parameters of lattice-ladder filter. Developed neural network training algorithm is optimal in terms of minimal number of constants, multiplication and addition operations, while the regularity of the structure is also preserved. For the financial support author would like to thank prof. L. Ljung (Link&ouml;ping University, Sweden), The Royal Swedish Academy of Sciences and The Swedish Institute - New Visby project Ref. No. 2473/2002 (381/T81).
A model for software rework reduction through a combination of anomaly metrics
Authors: Lars-Ola Damm, Lars Lundberg, Claes Wohlin
Venue: Journal of Systems and Software (2008)

Analysis of anomalies reported during testing of a project can tell a lot about how well the processes and products work. Still, organizations rarely use anomaly reports for more than progress tracking although projects commonly spend a significant part of the development time on finding and correcting faults. This paper presents an anomaly metrics model that organizations can use for identifying improvements in the development process, i.e. to reduce the cost and lead-time spent on rework-related activities and to improve the quality of the delivered product. The model is the result of a four year research project performed at Ericsson.
Perceptually guided level of detail techniques
Authors: Gary W. Meyer
Venue:  (2008)

Finding a compact polygonal representation of a geometric object is an important problem for computer graphics. Until recently, most of the effort has been focused on finding a simplified polygonal mesh that is geometrically similar to the original mesh. In this thesis, we develop algorithms with an emphasis on finding a compact representation that is visually similar to the original geometric object. First, we propose the concept of a faceting signal, which characterizes the faceted appearance of a polygonal model under different viewing distances, viewing directions, lighting conditions, etc. We further analyze its properties in the frequency domain. A perceptual metric is proposed that indicates the visibility of the faceting signal. The importance of this analysis is illustrated by a perceptually guided surface texturing algorithm and a geometric level of detail management system. Second, we propose a perceptually guided remeshing algorithm that automatically distributes samples over a polygon mesh by taking the visual perceptual properties of the appearance data into account during the remeshing process. Due to the properties of the human visual system, especially visual masking, the artifacts in the final rendered mesh are invisible to the human observer. The approach also improves the quality of the images in a budget based system since the distribution of polygons across all of the objects in a scene is guided by the principles of visual perception. Third, we develop a mesh simplification algorithm that is guided by the masking potential of its surface textures. A masking importance value is determined for each vertex of the original mesh, and this value is used to weight the geometric error in a geometry based simplification algorithm. Our mesh simplification algorithm takes into account both the geometry of the object and the masking potential of its surface textures. We also present a rendering algorithm for textured point based models that takes into account the masking properties of the human visual system. In our system, high quality textures are mapped onto point-based models. Given a texture, its importance map is first computed by an algorithm inspired by the visual masking tool included in the JPEG2000 standard. This importance map indicates the masking potential of the texture. During runtime, point-based models are simplified and rendered according to this computed importance. Finally, we propose to use a visual discrimination metric to determine the resolution requirement of a texture for rendering. A visual discrimination metric is first used to compute a curve that represents the visual distortion-vs-resolution of a texture. Given a visual distortion threshold, the resolution of the texture can be determined based on the distortion-vs-resolution curve.