ppxscal/embedding_network huggingface dataset:
Detecting Repeat Families in Incompletely Sequenced Genomes
Authors: José Augusto Amgarten Quitzau, Jens Stoye
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

Repeats form a major class of sequence in genomes with implications for functional genomics and practical problems. Their detection and analysis pose a number of challenges in genomic sequence analysis, especially if the genome is not completely sequenced. The most abundant and evolutionary active forms of repeats are found in the form of families of long similar sequences. We present a novel method for repeat family detection and characterization in cases where the target genome sequence is not completely known. Therefore we first establish the sequence graph, a compacted version of sparse de Bruijn graphs. Using appropriate analysis of the structure of this graph and its connected components after local modifications, we are able to devise two algorithms for repeat family detection. The applicability of the methods is shown for both simulated and real genomic data sets.
The Network of Reference Frames Theory: A Synthesis of Graphs and Cognitive Maps
Authors: Tobias Meilinger
Venue: Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space (2008)

The network of reference frames theory explains the orientation behavior of human and non-human animals in directly experienced environmental spaces, such as buildings or towns. This includes self-localization, route and survey navigation. It is a synthesis of graph representations and cognitive maps, and solves the problems associated with explaining orientation behavior based either on graphs, maps or both of them in parallel. Additionally, the theory points out the unique role of vista spaces and asymmetries in spatial memory. New predictions are derived from the theory, one of which has been tested recently.
Safety Assurance Strategies for Autonomous Vehicles
Authors: Andrzej Wardziński
Venue: Proceedings of the 27th international conference on Computer Safety, Reliability, and Security (2008)

Assuring safety of autonomous vehicles requires that the vehicle control system can perceive the situation in the environment and react to actions of other entities. One approach to vehicle safety assurance is based on the assumption that hazardous sequences of events should be identified during hazard analysis and then some means of hazard avoidance and mitigation, like barriers, should be designed and implemented. Another approach is to design a system which is able to dynamically examine the risk associated with possible actions and then select the safest action to carry it out. Dynamic risk assessment requires maintaining the situation awareness and prediction of possible future situations. We analyse how these two approaches can be applied for autonomous vehicles and what strategies can be used for safety argumentation. 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
Estimating Local Cardinalities in a Multidimensional Multiset
Authors: Patrick Truong, Fabrice Guillemin
Venue: Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management (2007)

In connection with port scan and worm propagation in the Internet, we address in this paper the problem of estimating the ber of destinations communicating with a given source. We propose a computational and memory-efficient technique of finding the top-talker sources. The proposed algorithm is tested against actual data (NetFlow records from the interconnection IP backbone network of France Telecom).
Ordering Process of Self-Organizing Maps Improved by Asymmetric Neighborhood Function
Authors: Takaaki Aoki, Kaiichiro Ota, Koji Kurata, Toshio Aoyagi
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

The Self-Organizing Map (SOM) is an unsupervised learning method based on the neural computation, which has recently found wide applications. However, the learning process sometime takes multi-stable states, within which the map is trapped to a undesirable disordered state including topological defects on the map. These topological defects critically aggravate the performance of the SOM. In order to overcome this problem, we propose to introduce an asymmetric neighborhood function for the SOM algorithm. Compared with the conventional symmetric one, the asymmetric neighborhood function accelerates the ordering process even in the presence of the defect. However, this asymmetry tends to generate a distorted map. This can be suppressed by an improved method of the asymmetric neighborhood function. In the case of one-dimensional SOM, it found that the required steps for perfect ordering is numerically shown to be reduced from O(N 3) to O(N 2).
Learning from House-Hunting Ants: Collective Decision-Making in Organic Computing Systems
Authors: Arne Brutschy, Alexander Scheidler, Daniel Merkle, Martin Middendorf
Venue: Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence (2008)

This paper proposes ant-inspired strategies for self-organized and decentralized collective decision-making in computing systems which employ reconfigurable units. The particular principles used for the design of these strategies are inspired by the house-hunting of the ant Temnothorax albipennis. The considered computing system consists of two types of units: so-called worker units that are able to execute jobs that come into the system, and scout units that are additionally responsible for the reconfiguration process of all units. The ant-inspired strategies are analyzed experimentally and are compared to a non-adaptive reference strategy. It is shown that the ant-inspired strategies lead to a collective decentralized decision process through which the units are able to find good configurations that lead to a high system throughput even in complex configuration spaces.
An Efficient Algorithm for the Inclusion Problem of a Subclass of DPDAs
Authors: Ryo Yoshinaka
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

This paper presents an efficient algorithm solving the inclusion problem of a new subclass of context-free languages. The languages are accepted by the special kind of real-time deterministic pushdown automata, called strongly forward-deterministic pushdown automata, that go to the same state and push the same sequence of stack symbols whenever transition is allowed on the same input symbol. Our algorithm can be applied to efficient identification in the limit of that class from positive data. 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
Case-Based Reasoning in the Health Sciences: Why It Matters for the Health Sciences and for CBR
Authors: Isabelle Bichindaritz
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

Biomedical domains have been an application domain of choice for artificial intelligence (AI) since its pioneering years in expert systems. Some simple explanations to this phenomenon are the intellectual complexity presented by this domain, as well as the dominant industry market share of healthcare. Following in AI's tracks, case-based reasoning (CBR) has been abundantly applied to the health sciences domain and has produced an excellent as well as varied set of publications, which has fostered CBR research innovation to answer some of the research issues associated with this intricate domain. Some notable examples are synergies with other AI methodologies, and in particular with ontologies [8] and with data mining, the study of the temporal dimension in CBR, the processing of multimedia cases, and novel tasks for CBR such as parameter setting. However CBR has a major endeavor to take on in the health sciences: how to position itself with regard to statistics for studying data? Some claim that CBR proposes an alternative viewpoint on the concept of evidence in biomedicine; others that CBR and statistics complement one another in this domain. In any case, an interesting question to study is whether CBR could become one day as fundamental to the health sciences as statistics is today? This question in particular broadens the health sciences challenge to a universal scope.
Mathematical Software in Basic Evaluation of Definite Integrals
Authors: David Kahaner, Webb Wyman
Venue: IEEE Micro (1983)

This program for the numerical approximation of definite integrals has been tested in several microcomputer environments. It is competitive with similar mathematical software in Fortran.
A Dipolar Competitive Neural Network for Video Segmentation
Authors: R. M. Luque, D. López-Rodríguez, E. Dominguez, E. J. Palomo
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

This paper present a video segmentation method which separate pixels corresponding to foreground from those corresponding to background. The proposed background model consists of a competitive neural network based on dipoles, which is used to classify the pixels as background or foreground. Using this kind of neural networks permits an easy hardware implementation to achieve a real time processing with good results. The dipolar representation is designed to deal with the problem of estimating the directionality of data. Experimental results are provided by using the standard PETS dataset and compared with the mixture of Gaussians and background subtraction methods.
Multiphysics Technologies
Authors: Michael A. Gray
Venue: Computing in Science and Engineering (2008)

Currently available tools can help establish a common interface for various problem solvers in different fields. By integrating these tools, researchers can start bringing together the best work in science and engineering, perhaps forging an entirely new field.
Algorithmic Challenges for Systems-Level Correlational Analysis: A Tale of Two Datasets
Authors: Michael A. Langston
Venue: Proceedings of the 10th international workshop on Algorithms and Data Structures (2007)

I will discuss novel algorithmic, combinatorial and correlational tools for the analysis of complex natural systems. A pair of illustrative but widely divergent applications will be described. Despite huge differences in data acquisition methodologies, the algorithmic missions for both problems are similar, and help to highlight the rich interplay between data quality and effective computation.
Graph-based approximation algorithms for cooperative routing problems
Authors: Joao P. Hespanha
Venue:  (2008)

This work focuses on finding good approximations to large scale, computationally complex cooperative routing problems. These optimizations may be defined on a graph, or a continuous domain on which we construct a graph. In the latter case, we show that the construction of the graph is a key step in the approximation algorithm and is vital to its performance. The remainder of this work is a combination of two differing approaches to the approximation of cooperative routing graph optimizations. In each case, the goal is the same: find fast approximation algorithms that generate close-to-optimal solutions. The first method, which we call fractal decomposition, works by recursively partitioning the graph in order to reduce the original large problem to several smaller problems. The solutions to these smaller problems are used to construct bounds on the optimal solution and generate an approximate solution. This general method applies to a wide range of graph optimizations for which the data is static, including shortest path, maximum flow, and graph search. As the number of decomposition levels increases, the computational complexity approaches O(n) at the expense of looser approximation bounds. We demonstrate the fractal decomposition method on three example problems related to cooperative routing: shortest path matrix, maximum flow matrix, and cooperative search. Large-scale simulations show that this fractal decomposition method is computationally fast and can yield good results for practical problems. The second approximation method is a receding horizon approach applied to a search problem, in which multiple agents are cooperatively searching for a mobile target in a bounded continuous region. By sampling the region of interest at locations with high target probability, we reduce the continuous search problem to an optimization on a finite graph. Paths are computed on this graph using a receding horizon approach, in which the horizon is a fixed number of waypoints. To facilitate a fair comparison between paths of varying length on a non-uniform graph, we use an optimization criterion corresponding to the probability of finding the target per unit time. Using this algorithm, we show that the team discovers the target in finite time with probability one. Simulations show that this algorithm makes efficient use of agents and performs quite well compared to previously proposed cooperative search algorithms.
Immune Responses: A Stochastic Model
Authors: Anastasio Salazar-Bañuelos
Venue: Proceedings of the 7th international conference on Artificial Immune Systems (2008)

Immune phenomena are explained from the reductionist view of the immune system as a collection of cells, molecules, and their interactions. Although this approach has produced abundant valuable information, it has added increased complexity. Artificial Immune Systems (AIS) have relied on this theoretical framework to emulate the desired characteristics of immunity. However, the complexity of the theoretical base has lead to an impasse in AIS research, suggesting that a new theoretical framework is needed. A theoretical model is presented here that explains immune responses as a "swarm function". The model proposes a system based on two stochastic networks: a central recursive network, wherein the proportion of agents is determined and maintained, and a peripheral network, wherein the random interactions of these agents determine if an inflammatory response will emerge from the system. 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
Safe Modification of Pointer Programs in Refinement Calculus
Authors: Susumu Nishimura
Venue: Proceedings of the 9th international conference on Mathematics of Program Construction (2008)

This paper discusses stepwise refinement of pointer programs in the framework of refinement calculus. We augment the underlying logic with formulas of separation logic and then introduce a pair of new predicate transformers, called separating assertion and separating assumption. The new predicate transformers are derived from separating conjunction and separating implication, which are fundamental logical connectives in separation logic. They represent primitive forms of heap allocation/deallocation operators and the basic pointer statements can be specified by means of them. We derive several refinement laws that are useful for stepwise refinement and demonstrate the use of the laws in the context of correctness preserving transformations that are intended for improved memory usage.The formal development is carried out in the framework of higher-order logic and is based on Back and Preoteasa's axiomatization of state space and its extension to the heap storage [BP05, Pre06]. All the results have been implemented and verified in the theorem prover PVS.
A Visual Framework for the Definition and Execution of Reverse Engineering Processes
Authors: Andrea Lucia, Michele Risi, Luigi Rizzi, Giuseppe Scanniello
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

In this paper we present a visual framework developed as an Eclipse plug-in to define and execute reverse engineering processes aimed at comprehending traditional and web based information systems. Processes are defined in terms of UML activity diagrams, where predefined or newly developed software components can be associated to each activity. Components implemented using either traditional programming languages or software environments for data analysis (i.e., MATLAB or R) can be reused. Once the process has been fully defined the software engineer executes it to reverse engineering and comprehend software systems. The proposed visual framework has been evaluated on two case studies.
Accessibility: Education for Web Design and E-Learning Introduction to the Special Thematic Session
Authors: Jenny Craven, Joachim Klaus
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

There is a clear role for accessibility assessment tools, standards and guidelines to help web designers, application developers and those who use and support web-based services. However, some aspects of web accessibility cannot be objectively tested by automated tools or by simple adherence to standards and guidelines. The application of expert judgment is required and thus accessibility needs to be addressed through more formal education and training. Programmes exist which advocate, and raise the profile of accessibility but most of these are only offered locally, with widely differing scope and complexity. There is a lack of a common European or even international curriculum in the vital area of education and training for web accessibility and design. Therefore, this Special Thematic Session will bring together stakeholders such as educators, e-Learning providers, and researchers to share their knowledge and expertise.
Ontological Profiles in Enterprise Search
Authors: Geir Solskinnsbakk, Jon Atle Gulla
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

Ontology-driven search applications use ontological concepts either to index documents or to guide and understand the users. Since ontologies by nature are domain-dependent and application-independent, though, there is no guarantee that their concepts are efficient in categorizing and retrieving information from a specific document index. This paper explains the idea of ontological profiles, which is an ontology adapted to the actual language used in a document collection or among the users. A method for constructing ontological profiles from petroleum documents is presented, as well as a search application that makes use of profiles to interpret users' queries. Testing on real documents with a 20,000 concepts petroleum ontology reveals that the approach is useful in situations where recall is more critical than precision.
The effect of data structures modifications on algorithms for reasoning operations using a conceptual graphs knowledge base
Authors: Roger T. Hartley
Venue:  (2007)

Knowledge representation (KR) is used to store and retrieve meaningful information. Meaning cannot be directly stored in the computer; therefore, a series of levels of representation transforms knowledge to a format that a computer can process. This transformed knowledge is saved using dynamic data structures that are suitable for the style of KR being implemented, and through the KR the system manipulates the knowledge in the data using reasoning operations. The data structure, together with the contents of the transformed knowledge, is called the knowledge base (KB). An algorithm and the associated data structures make up the reasoning operation, and the performance of this operation is dependent on the KB it uses. In this work, the basic reasoning operations for knowledge management will be explored using a particular style of KR called Conceptual Graphs (CGs). These operations, projection and maximal join, are the foundation for query/answer and hypothesis generation (abduction) systems, respectively. It is believed that changing the reasoning operation's algorithm and providing adequate data structures for them can improve the implementation of the operation for use in intelligent systems; therefore, making them faster and more efficient. Different algorithms and data structures execution times are analyzed over the most general form of CGs knowledge base showing that flexible, fast and efficient operations can improve higher level systems.
Software Architectures for Task-Oriented Computing
Authors: David Garlan
Venue: Proceedings of the 1st European conference on Software Architecture (2007)

Recent advances in ubiquitous computing and artificial intelligence have led to a desire to better support user-oriented tasks by placing more intelligence in the computing infrastructure. This infrastructure helps mediate between computing resources and legacy applications on the one hand, and a user's high-level goals on the other hand. In this talk I survey recent research in developing software architectures to support these new capabilities. Key features of these architectures are the ability to interface with legacy applications, but still add considerable support for user tasks; the ability to incorporate machine learning so that the system adapts to the user over time; and the ability to cope with resource variability and user mobility. I outline some of the consequent software engineering challenges that arise in this setting.
Efficient Feature Selection for PTR-MS Fingerprinting of Agroindustrial Products
Authors: Pablo M. Granitto, Franco Biasioli, Cesare Furlanello, Flavia Gasperi
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

We recently introduced the Random Forest - Recursive Feature Elimination (RF-RFE) algorithm for feature selection. In this paper we apply it to the identification of relevant features in the spectra (fingerprints) produced by Proton Transfer Reaction - Mass Spectrometry (PTR-MS) analysis of four agro-industrial products (two datasets with cultivars of Berries and other two with typical cheeses, all from North Italy). The method is compared with the more traditional Support Vector Machine - Recursive Feature Elimination (SVM-RFE), extended to allow multiclass problems. Using replicated experiments we estimate unbiased generalization errors for both methods. We analyze the stability of the two methods and find that RF-RFE is more stable than SVM-RFE in selecting small subsets of features. Our results also show that RF-RFE outperforms SVM-RFE on the task of finding small subsets of features with high discrimination levels on PTR-MS datasets.
Simulation of Negotiation Policies in Distributed Multiagent Resource Allocation
Authors: Hylke Buisman, Gijs Kruitbosch, Nadya Peek, Ulle Endriss
Venue: Engineering Societies in the Agents World VIII: 8th International Workshop, ESAW 2007, Athens, Greece, October 22-24, 2007, Revised Selected Papers (2008)

In distributed approaches to multiagent resource allocation, the agents belonging to a society negotiate deals in small groups at a local level, driven only by their own rational interests. We can then observe and study the effects such negotiation has at the societal level, for instance in terms of the economic efficiency of the emerging allocations. Such effects may be studied either using theoretical tools or by means of simulation. In this paper, we present a new simulation platform that can be used to compare the effects of different negotiation policies and we report on initial experiments aimed at gaining a deeper understanding of the dynamics of distributed multiagent resource allocation.