ppxscal/embedding_network huggingface dataset:
A Study of the Major Graph Labelings of Trees
Authors: Auparajita Krishnaa
Venue: Informatica (2004)

Tree is one of the most studied and practically useful classes of graphs and is the attention of a great number of studies. There is absence of generalized results for tree as a class and even for one kind of labeling as whole. Only specialized results exist limited to specific types of trees only. A number of conjectures stand being unsolved. Graham and Sloane (1980) conjectured trees to be Harmonious and Ringel-Kotzig conjectured trees to be Graceful about three decades ago. Kotzig and Rosa (1970) ask the question whether all trees are Magic or not. No generalized result for Antimagic labeling is given for trees so far. This paper presents the methodologies to obtain the major labeling schemes for trees viz., Harmonious, Sequential, Felicitous, Graceful, Antimagic and found the trees to be not Magic except T(2,1), thus solving the said conjectures. These findings could also be useful for those working in fields where graphs serve as models.
Performance-Based Bayesian Learning for Resource Collaboration Optimization in Manufacturing Grid
Authors: Jian Zhou, Qing Li, Jim Browne, Qing Wang, Paul Folan, Tianyuan Xiao
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

Following the rapid development of Grid computing, Grid technology has been introduced into the manufacturing realm and is contemporarily being considered for the sharing of manufacturing resources. However current research in the subject-area is still immature and mainly focuses on conceptual framework development. Here a concrete performance-based Bayesian method for resource collaboration optimization in Extended Enterprise is proposed which improves and promotes research in applying Grid-thinking in inter-organizational manufacturing value chains. Based on the research background, problem statement, and the consideration of Bayesian learning, the method for probability dependency relationship modeling between the performance values of different manufacturing resource nodes in the Extended Enterprise is analysed; and is subsequently complimented by the development of an extended method for more general use. Finally, a system dynamics simulation model for the proposed method is established and the validity and effectivity of the suggested method is tested via a simple case study.
Comparing Posturographic Time Series through Events Detection
Authors: Juan Alfonso Lara, Guillermo Moreno, Aurora Pérez, Juan Pedro Valente, África López-Illescas
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

The comparison of two time series and the extraction of subsequences that are common to the two is a complex data mining problem. Many existing techniques, like the Discrete Fourier Transform (DFT), offer solutions for comparing two whole time series. Often, however, the important thing is to analyse certain regions, known as events, rather than the whole times series. This applies to domains like the stock market, seismography or medicine. In this paper, we propose a method for comparing two time series by analysing the events present in the two. The proposed method is applied to time series generated by stabilometric and posturographic systems within a branch of medicine studying balance-related functions in human beings.
Meta Comments for Summarizing Meeting Speech
Authors: Gabriel Murray, Steve Renals
Venue: Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction (2008)

This paper is about the extractive summarization of meeting speech, using the ICSI and AMI corpora. In the first set of experiments we use prosodic, lexical, structural and speaker-related features to select the most informative dialogue acts from each meeting, with the hypothesis being that such a rich mixture of features will yield the best results. In the second part, we present an approach in which the identification of "meta-comments" is used to create more informative summaries that provide an increased level of abstraction. We find that the inclusion of these meta comments improves summarization performance according to several evaluation metrics.
Keeping Offline Computer Usage Private
Authors: Michael Caloyannides
Venue: IEEE Security and Privacy (2003)

Protecting the confidentiality of computer usage involves far more than merely protecting the content of individual files. Going to extremes will not protect a computer from every threat, but it's nearly as close as we can get. 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
A Fast Approach to Segmentation of PET Brain Images for Extraction of Features
Authors: Xiaohong Gao, John Clark
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

Position Emission Tomography (PET) is increasingly applied in the diagnosis and surgery in patients thanks to its ability of showing nearly all types of lesions including tumour and head injury. However, due to its natures of low resolution and different appearances as a result of different tracers, segmentation of lesions presents great challenges. In this study, a simple and robust algorithm is proposed via additive colour mixture approach. Comparison with the other two methods including Bayesian classified and geodesic active contour is also performed, demonstrating the proposed colouring approach has many advantages in terms of speed, robustness, and user intervention. This research has many medical applications including pharmaceutical trials, decision making for drug treatment or surgery and patients follow-up and shows potential to the development of content-based image databases when coming to characterise PET images using lesion features.
Evaluation of Fluid-Thermal Systems by Dynamic Data Driven Application Systems - Part II
Authors: D. Knight, Q. Ma, T. Rossman, Y. Jaluria
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

A Dynamic Data Driven Application Systems (DDDAS) me-thodology is developed for evaluation of fluid-thermal systems wherein a complete specification of the boundary conditions is not known a priori and experimental diagnostics are restricted to a limited region of the flowfield. The Closed Loop formulation of DDDAS is used whereby experiment and simulation are synergized in an iterative manner to determine the unknown boundary conditions, thereby enabling a full simulation (and hence, evaluation) of the fluid-thermal system. In this DDDAS methodology, the experiment directs the simulation and vice-versa. The DDDAS methodology is applied to a heated jet injected into a laminar boundary layer where the jet temperature and velocity are not known a priori for the simulations. The DDDAS methodology accurately determines the unknown jet temperature and velocity.
Acquiring Word Similarities with Higher Order Association Mining
Authors: Sutanu Chakraborti, Nirmalie Wiratunga, Robert Lothian, Stuart Watt
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

We present a novel approach to mine word similarity in Textual Case Based Reasoning. We exploit indirect associations of words, in addition to direct ones for estimating their similarity. If word A co-occurs with word B, we say A and B share a first order association between them. If A co-occurs with B in some documents, and B with C in some others, then A and C are said to share a second order co-occurrence via B. Higher orders of co-occurrence may similarly be defined. In this paper we present algorithms for mining higher order co-occurrences. A weighted linear model is used to combine the contribution of these higher orders into a word similarity model. Our experimental results demonstrate significant improvements compared to similarity models based on first order co-occurrences alone. Our approach also outperforms state-of-the-art techniques like SVM and LSI in classification tasks of varying complexity.
Polytypic programming in COQ
Authors: Wendy Verbruggen, Edsko de Vries, Arthur Hughes
Venue: Proceedings of the ACM SIGPLAN workshop on Generic programming (2008)

The aim of our work is to provide an infrastructure for formal proofs over Generic Haskell-style polytypic programs. For this goal to succeed, we must have a definition of polytypic programming which is both fully formal and as close as possible to the definition in Generic Haskell. In this paper we show a formalization in the proof assistant Coq of type and term specialization. Our definition of term specialization can be interpreted as a formal proof that the result of term specialization has the type computed by type specialization.
Kernel-Based Inductive Transfer
Authors: Ulrich Rückert, Stefan Kramer
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

Methods for inductive transfer take advantage of knowledge from previous learning tasks to solve a newly given task. In the context of supervised learning, the task is to find a suitable bias for a new dataset, given a set of known datasets. In this paper, we take a kernel-based approach to inductive transfer, that is, we aim at finding a suitable kernel for the new data. In our setup, the kernel is taken from the linear span of a set of predefined kernels. To find such a kernel, we apply convex optimization on two levels. On the base level, we propose an iterative procedure to generate kernels that generalize well on the known datasets. On the meta level, we combine those kernels in a minimization criterion to predict a suitable kernel for the new data. The criterion is based on a meta kernel capturing the similarity of two datasets. In experiments on small molecule and text data, kernel-based inductive transfer showed a statistically significant improvement over the best individual kernel in almost all cases.
Gem #14: interrupt handling idioms (part 2)
Authors: Pat Rogers
Venue: ACM SIGAda Ada Letters (2008)

Ada Gem #14 -- There are two design idioms commonly used when handling interrupts with Ada. One has more of the characteristics associated with good software engineering, the other somewhat better performance. We explore these two idioms in this gem.
SEAGENT MAS platform development environment
Authors: Oǧuz Dikenelli
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: demo papers (2008)

SEAGENT is a goal-oriented MAS development platform developed by Ege University MAS research group. SEAGENT project was officially started in 2002. Its architecture evolved gradually till 2006 and then became stable and actively used within our research group.
Integration method and Runge-Kuuta method
Authors: Wannaporn Sanprasert, Ungsana Chundang, Maitree Podisuk
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

In [1], M. Podisuk, U. Chundang and W. Sanprasert introduced the integration method for finding the numerical solution of the initial value problem of ordinary differential equation which turned out to be the multi-step method. In this paper, the single step method of this integration method with the help of Gauss-Legendre Quadrature integration formula and the Taylor series expansion is explored. The results on some examples that include the initial value problem of fourth order of ordinary differential equation are shown. The comparison of these results are compared to the results that obtain by the Runge-Kutta method.
Colorization for Polarimetric SAR Image Based on Scattering Mechanisms
Authors: Qiming Deng, Yilun Chen, Weijie Zhang, Jian Yang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Polarimetric synthetic aperture radar (POLSAR) images are widely used for aerial and spatial image applications, such as terrain classification, target detection, etc. However, only monochrome gray images can be derived from SAR data due to the imaging mechanisms of SAR, which limits image presentation and visual appeal. In this paper, we proposed a new approach to colorization for POLSAR images. The basic principle is that pixels with the same scattering characteristics should have similar colors. To achieve this, the algorithm first utilizes the Cloude and Pottier's decomposition to separate pixels into eight scattering categories, and then unsupervised classification is applied for further iteration. Colorization is performed in Lab color space using the classification result, which assigns a color to each class according to the self-defined entropy-alpha color map. In this semiautomatic method, an operator only needs to define a color map, and then the indicated colors are automatically transferred to produce a fully colorized image. The effectiveness of this algorithm is demonstrated by a JPL/AIRSAR POLSAR image.
Application hardware-software co-design for reconfigurable computing systems
Authors: Tarek El-Ghazawi
Venue:  (2008)

Reconfigurable computing (RC) systems are composed of nodes with tightly coupled microprocessor(s) and field programmable gate arrays (FPGA). These systems provide unique application acceleration opportunities through the reconfigurability of the FPGA co-processor, which enables the customization of the hardware to the underlying applications and the processing synergy between the microprocessor and the FPGA. A formal methodology for hardware-software co-design, however, has not yet been established for the mapping of applications onto such reconfigurable systems. To the best of our knowledge, this is the first effort to formalize application co-design on reconfigurable computing systems. This research addresses the task of formalizing hardware-software co-scheduling for RC systems. Scheduling algorithms from related domains such as embedded computing (EC), heterogeneous computing (HC), and reconfigurable hardware (RH) were evaluated for their potential benefits to scheduling for RC. Selected algorithms from these domains were extended to provide scheduling capabilities for RC systems. The enhanced algorithms are analytically and experimentally shown to provide over one order of magnitude improvement in application throughput. The execution models of EC, HC, and RH, however, are quite different from that of RC systems and thus scheduling solutions were often not optimal. To address this, a formal co-design methodology and an efficient co-scheduling algorithm, Reconfigurable-Computing Co-Scheduling (ReCoS), has been proposed. The co-design methodology proposes a framework to identify an optimal co-schedule based on the available resources, constraints, and performance targets. The ReCoS algorithm is shown to provide up to one order of magnitude improvement over the enhanced scheduling algorithms from related domains for mapping applications onto an RC system. The proposed algorithms can be used by Hardware-Software compilers to deliver optimized solutions. They can also be used as the foundation for productivity tools that can guide users in Hardware-Software co-design of RC applications. To increase the usability and decrease the time necessary to co-design an application for an RC system, The Center for High-Performance Reconfigurable Computing (CHREC) Performance Analysis and Co-Design Tool (CHREC-PACT) was created. PACT provides application performance analysis, resource utilization, constraint analysis, and co-design assistance tools to quickly identify an optimal co-schedule between the microprocessor and its reconfigurable processor.
Universal Attribute Reduction Problem
Authors: Mikhail Ju. Moshkov, Marcin Piliszczuk, Beata Zielosko
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

In the paper, some generalizations of the notions of reduct and test (superreduct) are considered. The accuracy of greedy algorithm for construction of partial test is investigated. A lower bound on the minimal cardinality of partial reducts based on an information on greedy algorithm work is studied. Results of an experiment with greedy algorithm are described.
Searching for Complex Human Activities with No Visual Examples
Authors: Nazlı İkizler, David A. Forsyth
Venue: International Journal of Computer Vision (2008)

We describe a method of representing human activities that allows a collection of motions to be queried without examples, using a simple and effective query language. Our approach is based on units of activity at segments of the body, that can be composed across space and across the body to produce complex queries. The presence of search units is inferred automatically by tracking the body, lifting the tracks to 3D and comparing to models trained using motion capture data. Our models of short time scale limb behaviour are built using labelled motion capture set. We show results for a large range of queries applied to a collection of complex motion and activity. We compare with discriminative methods applied to tracker data; our method offers significantly improved performance. We show experimental evidence that our method is robust to view direction and is unaffected by some important changes of clothing.
Control of Hypothesis Space Using Meta-knowledge in Inductive Learning
Authors: Nobuhiro Inuzuka, Hiroyuki Ishida, Tomofumi Nakano
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

Inductive logic programming (ILP) is effective for classification learning because it constructs hypotheses combining background knowledge. On the other hand it makes the cost of search for hypothesis large. This paper proposes a method to prune hypothesis using a kind of semantic knowledge. When an ILP system uses a top-down search, after it visits a clause (rule) it explore another clause by adding a condition. The added condition may be redundant with other conditions in the clause or the condition may causes the body of clause unsatisfied. We study to represent and use to treat the redundancy and unsatisfactory of conditions as meta-knowledge of predicates. In this paper we give a formalism of meta-knowledge and show to use it with an ILP algorithm. We also study a method to generate meta-knowledge automatically. The method generates meta-knowledge which controls redundancy and contradiction with respect to predicates by testing properties extensionally.
Modeling Herds and Their Evolvements from Trajectory Data
Authors: Yan Huang, Cai Chen, Pinliang Dong
Venue: Proceedings of the 5th international conference on Geographic Information Science (2008)

A trajectory is the time-stamped path of a moving entity through space. Given a set of trajectories, this paper proposes new conceptual definitions for a spatio-temporal pattern named Herd and four types of herd evolvements: expand, join, shrink, and leave based on the definition of a related term flock. Herd evolvements are identified through measurements of Precision, Recall, and F-score. A graph-based representation, Herd Interaction Graph, or Herding, for herd evolvements is described and an algorithm to generate the graph is proposed and implemented in a Geographic Information System (GIS) environment. A data generator to simulate herd movements and their interactions is proposed and implemented as well. The results suggest that herds and their interactions can be effectively modeled through the proposed measurements and the herd interaction graph from trajectory data.
The Lightweight Runtime Engine of the Wireless Internet Platform for Mobile Devices
Authors: Yong-Duck You, Choong-Bum Park, Hoon Choi
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

This paper proposes a lightweight runtime engine that is the core part of the wireless Internet platform of mobiles devices such as cellular phones or PDAs. The proposed lightweight runtime engine downloads and executes mobile applications in the binary form. Its memory footprint is less than 100 Kbytes and consists of the lightweight scheduler module, memory management module, dynamic reconfiguration module, event handler module, and timer module. The lightweight scheduler can process events 13% faster than a competitive technique which is the widely used thread-based scheduler. The memory management module works 6 ~10 times faster than other memory management algorithms, and the proposed dynamic reconfiguration module also shows a good performance in reconfiguring the platform software.
Generic Reusable Concern Compositions
Authors: Aram Hovsepyan, Stefan Baelen, Yolande Berbers, Wouter Joosen
Venue: Proceedings of the 4th European conference on Model Driven Architecture: Foundations and Applications (2008)

The increasing complexity of software applications requires improved software development techniques in order to cope with, a.o., software reuse and evolution, the management of heterogeneous concerns, and the retargeting of systems towards new software platforms. The introduction of AOSD (aspect-oriented software development) and the support for MDD (model-driven development) are two important and promising evolutions that can contribute to better control of software complexity. In this paper we present an AOM (Aspect-Oriented Modeling) based framework to promote and enhance the reuse of concerns expressed in UML. We have developed a prototype composition engine implemented in ATL that can be used to compose concern models specified in UML.
Lady Lovelace and Charles Babbage
Authors: Velma R. Huskey, Harry D. Huskey
Venue: IEEE Annals of the History of Computing (1980)

This paper is centered on the correspondence that took place between Lady Lovelace and Charles Babbage, particularly during her writing of the extensive notes that accompany her translation of Menabrea's paper on Babbage's Analytical Engine. The material is selective. Her mathematical background and studies are given in some detail, while little mention is made of her other great interest, music. Her travels and family relationships are not mentioned except where they directly apply to her work or to her relationship with Charles Babbage. Most of the material has been gathered from original sources. Through the courtesy of the Rt. Hon. Earl of Lytton, O.B.E. (great-grandson of the Countess of Lovelace), and his son, Viscount Knebworth, access was granted to the Lovelace-Byron papers deposited in the Bodleian Library, Oxford University. The Babbage Correspondence in the British Library, London was another source. Also of value were the letters of the Somerville Collection owned by Lady Fairfax Lucy and deposited in the Bodleian Library.
Nuclear Reactor Reactivity Prediction Using Feed Forward Artificial Neural Networks
Authors: Shan Jiang, Christopher C. Pain, Jonathan N. Carter, Ahmet K. Ziver, Matthew D. Eaton, Anthony J. Goddard, Simon J. Franklin, Heather J. Phillips
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

In this paper, a feed forward artificial neural network (ANN) is used to predict the effective multiplication factor (k eff ), an indication of the reactivity of a nuclear reactor, given a fuel Loading Pattern (LP). In nuclear engineering, the k eff is normally calculated by running computer models, e.g. Monte Carlo model and finite element model, which can be very computationally expensive. In case that a large number of reactor simulations is required, e.g. searching for the optimal LP that maximizes the k eff in a solution space of 1010 to 10100, the computational time may not be practical. A feed forward ANN is then trained to perform fast and accurate k eff prediction, by using the known LPs and corresponding k eff s. The experiments results show that the proposed ANN provides accurate, fast and robust k eff predictions.