ppxscal/embedding_network huggingface dataset:
Factorial representations to generate arbitrary search distributions
Authors: Marc Toussaint
Venue: Proceedings of the 2005 workshops on Genetic and evolutionary computation (2005)

A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis to sample new search points. Existing algorithms learn the search distribution directly on the given problem representation. We ask how search distributions can be modeled indirectly by a proper choice of factorial genetic code. For instance, instead of learning a direct probabilistic model of the dependencies between variables (like BOA does), one can alternatively learn a genetic representation of solutions on which these dependencies vanish. We consider questions like: Can every distribution be induced indirectly by a proper factorial representation? How can such representations be constructed from data? Are specific generative representations, like grammars or L-systems, universal w.r.t. inducing arbitrary distributions? We will consider latent variable probabilistic models as a framework to address such questions and thereby also establish relations to machine learning concepts like ICA.
An efficient and fair cooperative approach for resource management in wireless networks: Research Articles
Authors: Jian Ye, Symeon Papavassiliou, Sirin Tekinay
Venue: Wireless Communications Mobile Computing (2005)

In cellular networks, the implementation of various resource management processes, such as bandwidth reservation and location updates, has been based on the one-to-one resource management information exchange paradigm, between the mobile nodes and the base stations. In this paper, we design and demonstrate the use of a distributed cooperative scheme that can be applied in the future wireless networks to improve the energy consumption for the routine management processes of mobile terminals, by adopting the peer-to-peer communication concept of wireless ad hoc networks. In our approach, the network is subdivided into one-hop ad hoc clusters where the members of each cluster cooperate to perform the required management functions, and conventional individual direct report transmissions of the mobile terminals to the base stations are replaced by two-hop transmissions. The performance evaluation and the corresponding numerical results presented in this paper confirm that our proposed scheme reduces significantly the overall system energy consumption when compared with the conventional one-to-one direct information management exchange approach. Furthermore the issue of fairness in dynamically selecting the various cluster heads in successive operational cycles of the proposed scheme is analyzed, and an enhanced algorithm is proposed and evaluated, which improves significantly the cluster head selection fairness, in order to balance the energy consumption among the various mobile terminals. Copyright &copy; 2005 John Wiley & Sons, Ltd.
Designing an SRE Program for Commercial Software Organizations
Authors: Will Snipes, John Hudepohl
Venue: Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (2005)

To maximize business value, commercial software organizations need to apply Software Reliability Engineering (SRE) using a distributed model where key practices are performed by different roles in the organization. SRE practitioners need to understand the landscape of software development in order to define a program that is effective at moving the organization towards higher reliability.
Randomness in proof complexity
Authors: Joshua Buresh-Oppenheim
Venue:  (2005)

This thesis focuses on the topic of propositional proof complexity, which is an area of study with deep connections to both mathematical logic and complexity theory. Three common propositional proof systems (or subsystems thereof) are considered: Resolution, bounded-depth Frege and Cutting Planes. Two uses of randomness for achieving lower bounds on these systems are explored, namely, using randomly generated tautologies as inputs to the proof systems, and using random restrictions to reason about the complexity of proofs of these tautologies. In particular, there are three main results. The first is an almost-complete characterization, in terms of relative size-complexity, of the six most popular refinements of Resolution. These refinements are important, both practically and theoretically, for automated theorem proving. The second main result represents substantial progress towards our understanding of the most fundamental tautology in proof complexity: the pigeonhole principle. The pigeonhole principle with parameters m and n states that m pigeons cannot be placed in n holes without collisions whenever m > n. As m gets bigger relative to n, the statement gets weaker and therefore easier to prove. We show that this tautology requires superpolynomial-size proofs in bounded-depth Frege whenever m is at most (1 + 1/polylog n) times n. The third main result analyzes cutting planes procedures, which are used primarily in combinatorial optimization, as propositional proof systems. It is shown that many rounds of the procedures due to Gomory and Chv&aacute;tal and to Lov&aacute;sz and Schrijver are required to prove the unsatisfiability of many CNF formulas, including random kCNFs and the (negation of the) Tseitin Tautologies. It follows that many rounds of these procedures are required to well-approximate the optimization problem MAXSAT.
Automatic Segmentation of Lung Areas Based on SNAKES and Extraction of Abnormal Areas
Authors: Yoshinori Itai, Hyoungseop Kim, Seiji Ishikawa, Shigehiko Katsuragawa, Takayuki Ishida, Katsumi Nakamura, Akiyoshi Yamamoto
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Segmentation for lung areas from CT images is important tasks on understanding tissue construction, computing and extracting abnormal areas. Recently, many segmentation methods based on contour model are presented. SNAKES (active contour model), on the other hand, are used extensively in computer vision and image processing applications particularly to locate the object boundaries. In lung segmentation, SNAKES is used for extracting the detail of ROI. However, a completely automatic segmentation method is not yet published, since it needs some manual efforts for initial contouring and constructing the contour models. In this paper, we propose a segmentation method for lung areas based on SNAKES without considering any manual operations. Furthermore, abnormal area including ground-glass opacity or lung cancer is classified by voxel density on the CT slice set. Experiment is performed employing nine thorax CT image sets and satisfactory results are obtained. Obtained results are shown along with a discussion.
Optimization frameworks for discrete composite laminate stacking sequences
Authors: Layne T. Watson
Venue:  (2005)

Composite panel structure optimization is commonly decomposed into panel optimization subproblems, with specified local loads, resulting in manufacturing incompatibilities between adjacent panel designs. Using genetic algorithms to optimize local panel stacking sequences allows panel populations of stacking sequences to evolve in parallel and send migrants to adjacent panels, so as to blend the local panel designs globally. The blending process is accomplished using the edit distance between individuals of a population and the set of migrants from adjacent panels. The objective function evaluating the fitness of designs is modified according to the severity of mismatches detected between neighboring populations. This lays the ground work for natural evolution to a blended global solution without leaving the paradigm of genetic algorithms. An additional method applied here for constructing globally blended panel designs uses a parallel decomposition antithetical to that of earlier work. Rather than performing concurrent panel genetic optimizations, a single genetic optimization is conducted for the entire structure with the parallelism solely within the fitness evaluations. A guide based genetic algorithm approach is introduced to exclusively generate and evaluate valid globally blended designs, utilizing a simple master-slave parallel implementation, implicitly reducing the size of the problem design space and increasing the quality of discovered local optima.
Fault-tolerant control in complex systems with real-time applications
Authors: Petros A. Ioannou
Venue:  (2005)

Designing and implementing a fault-tolerant control (FTC) system for large-scale systems pose a great challenge due to the high dimensionality, multiple inputs and outputs, and processor limitations. In this study, the problem of designing and implementing a decentralized FTC system is considered for large-scale systems. The decentralized FTC system consists of three schemes: decentralized nominal controller, decentralized fault detection and isolation, and decentralized supervision scheme. The proposed approach overcomes the design and implementation complexities by dividing the total task of the FTC system into a number of small tasks. These small tasks can be easily implemented by running a number of commercial processors in parallel. The proposed design is applied to a typical large-scale system: a segmented telescope test bed, which consists of 6 segments giving an overall high order system. The decentralized FTC system consists of 6 local units, each one responsible for controlling one segment, detecting and isolating faults, and reconfiguring the controller for fault accommodation. The algorithm of the 6 local units is implemented by running 3 processors in parallel. Real-time results demonstrate the capability of the proposed decentralized FTC system to tolerate sensor failure in large-scale systems such as in the segmented telescope test bed. In addition, since designing an FTC system to recover the original system performance is impractical in many situations, due to the new physical constraints caused by the fault, designing an FTC system with the ability to comply with the new physical constraints is considered for a class of nonlinear systems subject to actuator saturation fault. The approach is based on the conceptual tools of linear matrix inequalities and on-line fault model estimation. The FTC system consists of nominal control, fault diagnostic, and fault accommodation schemes. These schemes are designed to: (1) achieve stability and tracking requirements; (2) detect, isolate, and estimate a fault; and (3) reduce the fault effect on the system. A nonlinear model of an F16 aircraft longitudinal motion is used to demonstrate the effectiveness of the proposed FTC system.
Dynamic network analysis-based communication network evolution and shared situation awareness estimation in the network organization
Authors: John M. Graham
Venue:  (2005)

As the network organization proliferates over traditional hierarchical forms, the requirement to describe, estimate and predict the dynamic structure as well as the need to measure performance in network-organizations has become critical (Carley, 2002b; 2003). Traditional, static organizational line charts no longer produce viable explanations of organizational behavior. As a network, the members are constantly reorganizing to the environment and therefore are rapidly changing the organizational structure (Graham, Schneider, Gonzalez, 2004). These rapid shifts in organizational structure have implications for organizational performance and measurement. Measures of organizational performance include situation model (Entin Entin, 1999), mental model congruence (Entin Serfaty, 2000; Graham, Schneider, Bauer, Bessiere, Gonzalez, 2004), transactive memory (Carley Ren, 2001), shared mental model (Salas et al., 1995) and shared situation awareness (Endsley Jones, 2001; 2002). Each of these measures have, as a common characteristic, the ability to describes how &lsquo;in-sync&rsquo; the organizational membership is at a given point of time. Organizations operating in a fast-paced environment which are &lsquo;in-sync&rsquo;, tend to have higher levels of performance than those that are not (Salas et al., 1999; Arquilla Ronfeldt, 2002). To understand and describe rapid network change in terms of Shared Situation Awareness, I use a combined approach consisting of experimentation and simulation. I conduct multiple, large-scale experiments on military command and control network-organization structure in a pseudo-laboratory environment. Using dynamic network analysis techniques, I identify and characterize the factors that contribute to the change in structure of the organization. Network change factors found significant are homophilly, physical distance, communication network distance, and organizational structure. These empirically based factors are instantiated in new implementation of the proximity matrix in the ORA DyNet models (Carley et al., 2003).
A Flexible Specification Model based on XML for Parallel Applications
Authors: Cristina Enomoto, Marco Aurelio Amaral Henriques
Venue: Proceedings of the 17th International Symposium on Computer Architecture on High Performance Computing (2005)

This article introduces a new workflow specification model for parallel applications. Many parallel systems allow only the following basic flow control: (1) a coordinator task distributes the data among the worker tasks, (2) the worker tasks process the data in parallel and (3) the coordinator task gather all the results. In some systems the application execution flow is based on a dependence relationship among tasks, representing a directed acyclic graph (DAG). Even with this model it is not possible to execute some important parallel applications and, therefore, there is a need for a new specification model with more sophisticated flow controls that allow, for example, conditional branching and iterations at the level of task management. The purpose of this article is to present a proposal for a new parallel application specification model that provides new types of control structures and allows the implementation of a broader range of applications.
Efficient Flooding Control Suitable for Multiple Requests
Authors: Takahisa Okazaki, Hideo Kamada, Kazuhiko Kinoshita, Hideki Tode, Koso Murakami
Venue: Proceedings of the International Symposium on Applications on Internet (2006)

Flooding algorithm is a fundamental control mechanism to notify all the nodes of some information, to get desired information from all the nodes, or to reserve a route, and so on. Flooding algorithm has merits of robustness and optimality to solutions. However, flooding algorithm has problems which increase the processing time until finishing the flooding control, and cause congestion in the network. To solve these problems, we have proposed an efficient flooding algorithm based on a biotic growth process of primitive creatures like molds or microbes. However, this algorithm has a problem which increases the processing time in a heavily loaded network. In this paper, we extend this flooding algorithm based on a biotic propagation, by using priority queuing and aggregation mechanism of returned information.
Obtaining Best Parameter Values for Accurate Classification
Authors: Frans Coenen, Paul Leng
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

In this paper we examine the effect that the choice of support and confidence thresholds has on the accuracy of classifiers obtained by Classification Association Rule Mining. We show that accuracy can almost always be improved by a suitable choice of threshold values, and we describe a method for finding the best values. We present results that demonstrate this approach can obtain higher accuracy without the need for coverage analysis of the training data. Keywords: Classification, Association Rule Mining.
A Hybrid Algorithm for Dynamic Lightpath Protection in Survivable WDM Optical Networks
Authors: Vinh Trong Le, Son Hong Ngo, Xiaohong Jiang, Susumu Horiguchi, Yasushi Inoguchi
Venue: Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks (2005)

Dynamic lightpath protection in survivable WDM networks requires finding a pair of diverse routes (i.e., a primary route and a backup route that are link-disjoint) that form a cycle upon the arrival of a new connection request. In this paper, we propose a novel hybrid algorithm for this problem based on a combination of the mobile agents technique and genetic algorithms (GA). By keeping a suitable number of mobile agents in the network to cooperatively explore the network states and continuously report diverse routes into the routing tables, our new hybrid algorithm can promptly determine the first population of cycles for a new request based on the routing table of its source node, without requiring the time consuming process associated with current GA-based lightpath protection schemes. We furthermore improve the performance of our algorithm by introducing a more advanced fitness function. Extensive simulation studies on the ns-2 network simulator show that our hybrid algorithm achieve a significantly lower blocking probability and a smaller execution time than the conventional survivable routing algorithms.
Comparative experiments with a multiple model based adaptive controller for a SCARA type direct drive manipulator
Authors: M. Kemal Ciliz, M. Ömer Tuncay
Venue: Robotica (2005)

In this paper, different adaptive control algorithms will be experimentally tested on a two axis SCARA type direct drive robot arm, and the performance of these algorithms will be compared. Being a direct drive system, the nonlinear effects, arising from the dynamics of the manipulator under high velocities, are directly reflected in the control of the manipulator. This makes the manipulator a more efficient test bed for testing the efficiency of the proposed adaptive schemes. In the experiments, we used fast trajectories rather than slow ones to observe how the proposed controllers compensate the dynamic nonlinear effects of manipulator dynamics. We will test some known adaptive control algorithms given in the literature along with our proposed adaptive control scheme which makes use of multiple models.
Proactive Route Planning Based on Expected Rewards for Transport Systems
Authors: Naoto Mukai, Toyohide Watanabe, Jun Feng
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Route planning is one of the important tasks for transport systems. Appropriate policies for route selections improve not only profitability of transport companies but also convenience of customers. Traditional ways for establishing the policies depend on manual efforts based on statistical data of transports. Moreover, traditional route planning techniques are reactive, i.e., an optimization based on information provided in advance. It is difficult for the manual policies and the reactive planning techniques to adjust dynamic changes of transport trends for customers such as amount and direction of transport demands, i.e., drivers of transport vehicles must follow the policies provided in advance. Therefore, in this paper we show how the proactive route planning based on expected rewards for transport systems can be modeled as a reinforcement learning problem. And, we show how agents as transport vehicles acquire their policies for route selection autonomously and dynamically. The learning ability of transport trends enables transport vehicles to foresee the next destination which provides high rewards. Finally, we report simulation results and make the effectiveness of our proposal strategy clear.
Web Services Automatic Composition Based on QoS
Authors: Jiamao Liu, Ning Gu, Yuwei Zong, Zhigang Ding, Shaohua Zhang, Quan Zhang
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

Based on a Web service quality model, this paper proposes a Web services automatic composition approach that can enable end user to compose a Web service automatically. After modeling Web services with rules and eliminating semantics conflicts among model parameters, a deduced network is computed with the inputs given by end user. With the deduced network, we can find the composition plan whose QoS is optimal.
Kernel Matched Subspace Detectors for Hyperspectral Target Detection
Authors: Heesung Kwon, Nasser M. Nasrabadi
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

In this paper, we present a kernel realization of a matched subspace detector (MSD) that is based on a subspace mixture model defined in a high-dimensional feature space associated with a kernel function. The linear subspace mixture model for the MSD is first reformulated in a high-dimensional feature space and then the corresponding expression for the generalized likelihood ratio test (GLRT) is obtained for this model. The subspace mixture model in the feature space and its corresponding GLRT expression are equivalent to a nonlinear subspace mixture model with a corresponding nonlinear GLRT expression in the original input space. In order to address the intractability of the GLRT in the feature space, we kernelize the GLRT expression using the kernel eigenvector representations as well as the kernel trick where dot products in the feature space are implicitly computed by kernels. The proposed kernel-based nonlinear detector, so-called kernel matched subspace detector (KMSD), is applied to several hyperspectral images to detect targets of interest. KMSD showed superior detection performance over the conventional MSD when tested on several synthetic data and real hyperspectral imagery.
A Grid-Based Mobile Agent Collaborative Virtual Environment
Authors: Hoon Kang Neo, Kim Meow Liew, QingPing Lin
Venue: Proceedings of the 2005 International Conference on Cyberworlds (2005)

This paper describes a large-scale collaborative virtual environment architecture that has the capability of scaling across multiple geographically dispersed resources. The architecture consists of distributed mobile agents working cooperatively in supporting and managing the virtual environments. The mobile agents' tasks include managing persistency and consistency of the virtual worlds, maintaining reliability and efficiency of user interactions, ensuring security and integrity of data and systems, and so on. The mobile agents are autonomous and has the ability of migrating among hosts to maximize resource utilizations. Grid technologies and concepts are introduced into the architecture. These improvements allow the mobile agents to execute and communicate securely in multiple administrative domains. Grid-based scheduling components and polices are integrated to provide intelligent resource optimizations. Furthermore, a better load-balancing can be achieved by utilizing additional or more accurate information like data-user proximity and hosts' workload invariance etc. The result will be a more scalable and robust mobile agent architecture.
Dynamic creation of interactive mixed reality presentations
Authors: Krzysztof Walczak, Rafal Wojciechowski
Venue: Proceedings of the ACM symposium on Virtual reality software and technology (2005)

In this paper, we describe a method of dynamic creation of interactive presentations for Mixed Reality environments. The presentations are created automatically for collections of multimedia objects arbitrarily arranged in virtual presentation spaces stored in a database. Users can navigate between the spaces using Web and 3D multimedia contents. The objects in each space are presented through a presentation template, which determines both the visualization and the interaction aspects of the presentation. The possible user interactions are described using a novel language called MR-ISL. The presentation templates are coded in X?VRML, a high-level modeling language. The method can be used in various application domains. Examples discussed in the paper relate to presentation of cultural heritage and educational resources.