ppxscal/embedding_network huggingface dataset:
Coupled evolutionary shape optimization and reverse engineering in product design and virtual prototyping
Authors: Damir Vučina, Željan Lozina, Igor Pehnec
Venue: WSEAS TRANSACTIONS on SYSTEMS (2009)

Product development in highly competitive times frequently implies very short time-to-market deadlines and product designs that need to deliver high performance at low investment and operation costs. These conflicting objectives can sometimes be accomplished by starting from existing designs and optimizing for better performance defined by some set of excellence criteria. This paper develops a systematic procedure that starts by using a 3D scan of the existing design, defines an efficient shape parameterization for the part of the object that shall be redesigned, and develops an evolutionary shape optimization model. This is accompanied by developing a numerical workflow to handle this demanding process and an implementation that provides solutions in reasonable computer time. The workflow is developed based on existing specialized applications for geometric modeling, numerical analysis, finite-element simulations, and optimization, and therefore makes a rather heterogeneous system. It uses and runs different applications on the 'as-needed' basis and provides for corresponding synchronization and data mining. The procedure is in this paper applied to the optimum design of 2D airfoils for wind-turbine blades.
Online Charging for IMS-Based Inter-domain Composite Services
Authors: Minh Le, Frens Jan Rumph, George B. Huitema, Bert Jan Beijnum, L. J. Nieuwenhuis
Venue: Proceedings of the 6th International Workshop on Internet Charging and Qos Technologies: Network Economics for Next Generation Networks (2009)

In order to manage financial risks online charging of composite services is becoming increasingly important for service providers to support service delivery in inter-domain environments. The 3rd Generation Partnership Project (3GPP) has developed a framework for off-line and online charging of IMS-based services. At service level, delivery of composite services often involves many service providers, where each service provider is responsible for the delivery of one or more service components (e.g. access service, IMS communication service, content service, etc.). Current Online Charging System (OCS) specified by 3GPPP does not support an online charging function for composite services. This paper discusses a number of implications of online charging of composite services, in particular inter-domain composite services. It addresses important shortcomings of the current 3GPP online charging architecture and suggests a way to overcome these shortcomings. The contribution of this paper is twofold. Firstly, it proposes an information model to support charging of inter-domain composite services. The proposed information model is based on the NGOSS and SID concepts of the TeleManagement Forum. Secondly, it proposes additional functionalities required for existing OCS in IMS to handle online charging of inter-domain composite services.
Using summarization for automatic briefing generation
Authors: Inderjeet Mani, Kristian Concepcion, Linda Van Guilder
Venue: NAACL-ANLP 2000 Workshop on Automatic Summarization (2000)

We describe a system which automatically generates multimedia briefings from high-level outlines. The system uses summarization in content selection and creation, and in helping form a coherent narrative for the briefing. The approach does not require a domain knowledge base.
Analysis of Time-Varying EEG Based on Wavelet Packet Entropy
Authors: Minfen Shen, Jialiang Chen, Patch J. Beadle
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

To investigate the time-varying characteristics of the multi-channels electroencephalogram (EEG) signals with 4 rhythms, a useful approach is developed to obtain the EEG's rhythms based on the multi-resolution decomposition of wavelet transformation. Four specified rhythms can be decomposed from EEG signal in terms of wavelet packet analysis. A novel method for time-varying brain electrical activity mapping (BEAM) is also proposed using the time-varying rhythm for visualizing the dynamic EEG topography to help studying the changes of brain activities for one rhythm. Further more, in order to detect the changes of the nonlinear features of the EEG signal, wavelet packet entropy is proposed for this purpose. Both relative wavelet packet energy and wavelet packet entropy are regarded as the quantitative parameter for computing the complexity of the EEG rhythm. Some simulations and experiments using real EEG signals are carried out to show the effectiveness of the presented procedure for clinical use.
Study of Double SMO Algorithm Based on Attributes Reduction
Authors: Chen Chen, Liu Hong, Haigang Song, Xueguang Chen, Tiemin Hou
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

To solve the classification problem in data mining, this paper proposes double SMO algorithm based on attributes reduction. Firstly attributes reduction deletes irrelevant attributes (or dimensions) to reduce data amount, consequently the total calculation is reduced, the training speed is fastened and Classification mode is easy to understand. Secondly applying SMO algorithm on the sampling dataset to get the approximate separating hyperplane, and then we obtain all the support vectors of original dataset. Finally again use SMO algorithm on the support vectors to get the final separating hyperplane. It is shown in the experiments that the algorithm reduces the memory space, effectively avoids the noise points' effect on the final separating hyperplane and the precision of the algorithm is better than Decision Tree, Bayesian and Neural Network.
Partial Face Matching between Near Infrared and Visual Images in MBGC Portal Challenge
Authors: Dong Yi, Shengcai Liao, Zhen Lei, Jitao Sang, Stan Z. Li
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

The latest multi-biometric grand challenge (MBGC 2008) sets up a new experiment in which near infrared (NIR) face videos containing partial faces are used as a probe set and the visual (VIS) images of full faces are used as the target set. This is challenging for two reasons: (1) it has to deal with partially occluded faces in the NIR videos, and (2) the matching is between heterogeneous NIR and VIS faces. Partial face matching is also a problem often confronted in many video based face biometric applications.In this paper, we propose a novel approach for solving this challenging problem. For partial face matching, we propose a local patch based method to deal with partial face data. For heterogeneous face matching, we propose the philosophy of enhancing common features in heterogeneous images while reducing differences. This is realized by using edge-enhancing filters, which at the same time is also beneficial for partial face matching. The approach requires neither learning procedures nor training data. Experiments are performed using the MBGC portal challenge data, comparing with several known state-of-the-arts methods. Extensive results show that the proposed approach, without knowing statistical characteristics of the subjects or data, outperforms the methods of contrast significantly, with ten-fold higher verification rates at FAR of 0.1%.
A hybrid system combining Self Organizing Maps with Case Based Reasoning in Structural Assessment
Authors: L. E. Mujica, J. Vehí, J. Rodellar
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

A hybrid system which combines Self Organizing Maps and Case Based Reasoning is presented and apply to Structural Assessment. Self Organizing Maps are trained as a classification tool in order to organize the old cases in memory with the purpose of speeding up the Case Based Reasoning process. Three real structures have been used: An aluminium beam, a pipe section and a long pipe.
Spotlight On Spreadsheets, 2nd edition
Authors: Jennifer Gipp
Venue:  (2007)

These easy-to-follow, fun and visual books keep learners engaged and interested in what they are learning. Users are introduced to new concepts in the lessons and then gain valuable hands-on experience using these skills in a variety of cross-curricular scenarios. 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
Kalman Filters to Generate Customer Behavior Alarms
Authors: Josep Lluis de la Rosa, Ricardo Mollet, Miquel Montaner, Daniel Ruiz, Víctor Muòoz
Venue: Proceeding of the 2007 conference on Artificial Intelligence Research and Development (2007)

Aggressive marketing campaigns to attract new customers only covers customer churn, resulting in neither growth nor profitability. Retaining current customers, increasing their lifetime value, and reducing customer churn rates, thereby allowing greater efforts and resources to be dedicated to capturing new customers are the goals of a commercial director. But how can that loss be detected in time and avoided---or at least reduced? There is the 3A program to keep customers loyal, based on analyzed information from our customers, to construct an expert alarm agent and one-to-one retention actions. In this paper we show how to apply the Kalman filter and study how to configure it to predict the normal behavior of customers by projecting their consumption patterns into the future. Abnormal behavior detected by the Kalman filter triggers alarms that lead to commercial actions to avoid customer churn.
Equivalence of regular expressions over a partially commutative alphabet
Authors: A. S. Shoukourian
Venue: Cybernetics and Systems Analysis (2009)

The equivalence problem is considered for regular expressions over a partially commutative alphabet. The alphabet is decomposed into disjoint subsets of noncommutative elements. The special case of the problem when the cardinal number of only one subset is larger than 1 and the cardinal numbers of the other subsets are equal to 1 is proved to be algorithmically solvable.
Electrochemical behavior of copper and cobalt in post-etch cleaning solutions
Authors: S. Bilouk, L. Broussous, R. P. Nogueira, V. Ivanova, C. Pernel
Venue: Microelectronic Engineering (2009)

Cleaning is one of the key steps of the integration of self aligned barriers (SAB) in microelectronic devices for 32nm technology and below. It is hence important to investigate the impact of different cleaning solutions on the metallic components of SAB, mainly in which concerns their surface stability. In this sense, the electrochemical behavior of copper and cobalt was studied under potentiodynamic conditions in different aqueous solutions of glycolic acid (GA) with and without benzotriazole (BTA) inhibitor. It has been observed that the presence of glycolic acid induces a monotonic increase of copper corrosion and a slight decrease in the case of cobalt. The cobalt dissolution remains nonetheless very active and is shown to be governed by oxygen reduction reaction. The addition of BTA, a well-known corrosion inhibitor for copper has shown to be also effective in the case of Co surfaces, with a ca 15-fold reduction of the intrinsic Co corrosion current density. The possibility of galvanic coupling between both metals, supposed to enhance the Co dissolution, has also been qualitatively investigated and seems not to be a determinant factor in these conditions.
Multiobjectivization for parameter estimation: a case-study on the segment polarity network of drosophila
Authors: Tim Hohm, Eckart Zitzler
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

Mathematical modeling for gene regulative networks (GRNs) provides an effective tool for hypothesis testing in biology. A necessary step in setting up such models is the estimation of model parameters, i.e., an optimization process during which the difference between model output and given experimental data is minimized. This parameter estimation step is often difficult, especially for larger systems due to often incomplete quantitative data, the large size of the parameter space, and non-linearities in system behavior. Addressing the task of parameter estimation, we investigate the influence multiobjectivization can have on the optimization process. On the example of an established model for the segment polarity GRN in Drosophila, we test different multiobjectivization scenarios compared to a singleobjective function proposed earlier for the parameter optimization of the segment polarity network model. Since, instead of a single optimal parameter setting, a set of optimal parameter settings exists for this GRN, the comparison of the different optimization scenarios focuses on the capabilities of the different scenarios to identify optimal parameter settings showing good diversity in the parameter space. By embedding the objective functions in an evolutionary algorithm (EA), we show the superiority of the multiobjective approaches in exploring the model's parameter space.
Evaluation of the HPF/JA Extensions on Fujitsu VPP Using the NAS Parallel Benchmarks
Authors: Kae Asaoka, Akio Hirano, Yasuo Okabe, Masanori Kanazawa
Venue: Proceedings of the 4th International Symposium on High Performance Computing (2009)

We have ported 5 codes in APR's HPF implementation of NAS Parallel benchmark, so that it is conformable to HPF 2.0 and HPF/JA specification. The porting is done with the full usage of HPF 2.0 and HPF/JA new features, while the base Fortran codes remain almost unmodified. Then we have measured the performance of these benchmark codes on Fujitsu VPP800 by HPF/VPP compiler. We have achieved fairly good acceleration ratio for all codes except MG, and better absolute performance than NPB 2.3 parallel implementation with MPI for EP and BT.
Stable and scalable congestion control for high-speed heterogeneous networks
Authors: Dmitri Loguinov
Venue:  (2008)

For any congestion control mechanisms, the most fundamental design objectives are stability and scalability. However, achieving both properties are very challenging in such a heterogeneous environment as the Internet. From the end-users' perspective, heterogeneity is due to the fact that different flows have different routing paths and therefore different communication delays, which can significantly affect stability of the entire system. In this work, we successfully address this problem by first proving a sufficient and necessary condition for a system to be stable under arbitrary delay. Utilizing this result, we design a series of practical congestion control protocols (MKC and JetMax) that achieve stability regardless of delay as well as many additional appealing properties. From the routers' perspective, the system is heterogeneous because the incoming traffic is a mixture of short- and long-lived, TCP and non-TCP flows. This imposes a severe challenge on traditional buffer sizing mechanisms, which are derived using the simplistic model of a single or multiple synchronized long-lived TCP flows. To overcome this problem, we take a control-theoretic approach and design a new intelligent buffer sizing scheme called Adaptive Buffer Sizing (ABS), which based on the current incoming traffic, dynamically sets the optimal buffer size under the target performance constraints. Our extensive simulation results demonstrate that ABS exhibits quick responses to changes of traffic load, scalability to a large number of incoming flows, and robustness to generic Internet traffic.
List Point Arboricity of Dense Graphs
Authors: Lingyan Zhen, Baoyindureng Wu
Venue: Graphs and Combinatorics (2009)

Let G be a simple graph. The point arboricity &#x03c1;(G) of G is defined as the minimum number of subsets in a partition of the point set of G so that each subset induces an acyclic subgraph. The list point arboricity &#x03c1;l (G) is the minimum k so that there is an acyclic L-coloring for any list assignment L of G which |L(v)|&#x00a0;&#x2265;&#x00a0;k. So &#x03c1;(G)&#x00a0;&#x2264;&#x00a0;&#x03c1;l (G) for any graph G. Xue and Wu proved that the list point arboricity of bipartite graphs can be arbitrarily large. As an analogue to the well-known theorem of Ohba for list chromatic number, we obtain &#x03c1;l (G&#x00a0;+&#x00a0;K n )&#x00a0;=&#x00a0;&#x03c1;(G&#x00a0;+&#x00a0;K n ) for any fixed graph G when n is sufficiently large. As a consequence, if &#x03c1;(G) is close enough to half of the number of vertices in G, then &#x03c1;l (G)&#x00a0;=&#x00a0;&#x03c1;(G). Particularly, we determine that $$\rho_l(K_{2(n)})=\lceil \frac {2n}{3}\rceil$$, where K 2(n) is the complete n-partite graph with each partite set containing exactly two vertices. We also conjecture that for a graph G with n vertices, if $$\rho(G)\geq \frac {n} {3}$$then &#x03c1;l (G)&#x00a0;=&#x00a0;&#x03c1;(G).
A retailer's decision process when anticipating a vendor's temporary discount offer
Authors: F. J. Arcelus, T. P. M. Pakkala, G. Srinivasan
Venue: Computers and Industrial Engineering (2009)

This paper considers a profit-maximizing retailer's decision process when anticipating a vendor's offer of a temporary sale at a reduced price. The retailer is confronted with anticipation and discount periods of unknown length, within which to develop simultaneously the expected profit-maximizing ordering policy needed to purchase the items at the reduced price and the expected profit-maximizing pricing policy to dispose of the temporary sale also at a reduced price. The resulting policies are valid for any probability distribution used to model the uncertainty in the length of the discount period. Numerical examples illustrate the main features of the models.
IPTV distribution network access system using WiMAX and WLAN technologies
Authors: Miguel Garcia, Jaime Lloret, Miguel Edo, Raquel Lacuesta
Venue: Proceedings of the 4th edition of the UPGRADE-CN workshop on Use of P2P, GRID and agents for the development of content networks (2009)

The mobility and ubiquity for any type of device to access the IPTV network must be supplied by the service provider. The minimum bandwidth required in the access network to provide IPTV services jointly with the necessity to guarantee the Quality of Experience (QoE) to the user makes the need of algorithms to combine different wireless standards and technologies in the access network. In this paper, we propose a system that decides which type of wireless access network to connect with (for dual-band and tri-band devices) depending on the requirements of the IPTV client, the available networks, and some network parameters, such as the number of loss packets and packet delay, to provide the maximum QoE to the customer. The measurements taken in a real environment from the wireless networks allow us to know the weight of the parameters in the proposed algorithm.
On the likely number of solutions for the stable marriage problem
Authors: Craig Lennon, Boris Pittel
Venue: Combinatorics, Probability and Computing (2009)

An instance of a size-n stable marriage problem involves n men and n women, each individually ranking all members of opposite sex in order of preference as a potential marriage partner. A complete matching, a set of n marriages, is called stable if no unmatched man and woman prefer each other to their partners in the matching. It is known that, for every instance of marriage partner preferences, there exists at least one stable matching, and that there are instances with exponentially many stable matchings. Our focus is on a random instance chosen uniformly from among all (n!)2n possible instances. The second author had proved that the expected number of stable marriages is of order nlnn, while its likely value is of order n1/2−o(1) at least. In this paper the second moment of that number is shown to be of order (nlnn)2. The combination of the two moment estimates implies that the fraction of problem instances with roughly cnlnn solutions is at least 0.84. Whether this fraction is asymptotic to 1 remains an open question.
Spatial outlier detection in heterogeneous neighborhoods
Authors: Vandana P. Janeja, Vijayalakshmi Atluri
Venue: Intelligent Data Analysis (2009)

Spatial outlier detection approaches identify outliers by first defining a spatial neighborhood. However, existing approaches suffer from two issues: (1) they primarily consider autocorrelation alone in forming the neighborhood, but ignore heterogeneity among spatial objects. (2) they do not consider interrelationships among the attributes for identifying how distinct the object is with respect to its neighbors, but consider them independently (either single or multiple). As a result, one may not identify truly unusual spatial objects and may also end up with frivolous outliers. In this paper, we revisit the computation of the spatial neighborhood and propose an approach to address the above two issues. We begin our approach with identifying a spatially related neighborhood, capturing autocorrelation. We then consider interrelationships between attributes and multiple, multilevel distributions within these attributes, thus considering autocorrelation and heterogeneity in various forms. Subsequently, we identify outliers in these neighborhoods. Our experimental results in various datasets (North Carolina SIDS data, New Mexico Leukemia data, etc.) indicate that our approach indeed correctly identifies outliers in heterogeneous neighborhoods.
A Parallel Nonnegative Tensor Factorization Algorithm for Mining Global Climate Data
Authors: Qiang Zhang, Michael W. Berry, Brian T. Lamb, Tabitha Samuel
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

Increasingly large datasets acquired by NASA for global climate studies demand larger computation memory and higher CPU speed to mine out useful and revealing information. While boosting the CPU frequency is getting harder, clustering multiple lower performance computers thus becomes increasingly popular. This prompts a trend of parallelizing the existing algorithms and methods by mathematicians and computer scientists. In this paper, we take on the task of parallelizing the Nonnegative Tensor Factorization (NTF) method, with the purposes of distributing large datasets into each cluster node and thus reducing the demand on a single node, blocking and localizing the computation at the maximal degree, and finally minimizing the memory use for storing matrices or tensors by exploiting their structural relationships. Numerical experiments were performed on a NASA global sea surface temperature dataset and result factors were analyzed and discussed.
Novelty detection with application to data streams
Authors: Eduardo J. Spinosa, André Ponce de Leon F. de Carvalho, João Gama
Venue: Intelligent Data Analysis (2009)

This paper presents and evaluates an approach to novelty detection that addresses it as the problem of identifying novel concepts in a continuous learning scenario, as an extension to a single-class classification problem. OLINDDA, an OnLIne Novelty and Drift Detection Algorithm that implements this approach, uses efficient standard clustering algorithms to continuously generate candidate clusters among examples that were not explained by the current known concepts. Clusters complying with a validation criterion that takes cohesiveness and representativeness into account are initially identified as concepts. By merging similar concepts, OLINDDA may enhance the representation of some concepts as it advances toward its final goal of describing novel emerging concepts in an unsupervised way. The proposed approach is experimentally evaluated by the use of several measures taken throughout the learning process. Results show that it is capable of identifying novel concepts that are pure and correspond to real classes, disregarding unrepresentative clusters and outliers.