ppxscal/embedding_network huggingface dataset:
Ordering Grids to Identify the Clustering Structure
Authors: Shihong Yue, Miaomiao Wei, Yi Li, Xiuxiu Wang
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Almost all of the well-known clustering algorithms require input parameters while these parameters may be difficult to be determined. OPTICS (Ordering Points To Identify the Clustering Structure Cluster Structure) is a primary semi-clustering method to visualize the data structure and to determine the input parameters of a given clustering algorithm. However, OPTICS has too high complexity O(n 2 logn) to be applied to any large dataset of n data. In this paper, we present a new semi-clustering method by partitioning data space into a number of grids and Ordering all Grids To Identify the Clustering Structure (OGTICS). Accordingly, the new method is called OGTICS. The OGTICS has only linear complexity O(n) and thus is much faster than OPTICS. Consequently, the OGTICS can be applied to very large dataset.
Generalized complex structures on courant algebroids
Authors: James David Barton
Venue:  (2007)

In this thesis we study generalized complex structures defined on Lie bialgebroids, and arbitrary Courant algebroids. This thesis consists of two parts: the first deals with the generalized complex structures on Courant algebroids, while the second discusses generalized complex submanifolds. The basic examples of generalized complex structures are given, and certain classes of Poisson-Nijenhuis manifolds are described using generalized complex structures. The Poisson structure arising from a generalized complex structure is also defined explicitly. Generalized complex structures on arbitrary Courant algebroids are also described using generating operators and spinors. A generating operator for the Courant algebroid of a Lie bialgebroid is also given. In the second part we introduce the notion of twisted generalized complex submanifolds and describe an equivalent characterization in terms of Poisson-Dirac submanifolds. Our characterization recovers a result of Vaisman [38]. An equivalent characterization is also given in terms of spinors. As a consequence, we show that the fixed locus of an involution preserving a twisted generalized complex structure is a twisted generalized complex submanifold. Lastly, we also discuss generalized K&auml;hler submanifolds. 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
Affective Text Variation and Animation for Dynamic Advertisement
Authors: Carlo Strapparava, Alessandro Valitutti, Oliviero Stock
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

The largest part of the advertising market is already electronic. This means there is an opportunity for automatizing some of the production processes, such as producing and rendering catchy language expressions. A system is described that produces creative, affective variations of familiar textual expressions and animates them according to the affective contents. The textual variations are based on lexical semantics techniques such as an algorithm that looks for affective similarity, and on concepts such as optimal innovation, realized through assonant substitutions. Animation results from the realization of a scripting language for kinetic typography. The combination of affective variation and automatic affective perceptual rendering of key elements in the resulting expression is meant to guarantee effectiveness in advertising communication.
Cad technology for clothing biomechanical engineering design
Authors: Yi Li
Venue:  (2007)

The purpose of research is to establish a theoretical framework of integrated CAD system for clothing biomechanical engineering design by developing computer simulation and visualization platform. A mathematical model and visualization environment have been developed to simulate the dynamic mechanical interactions between clothing and human body during wear to reveal skin pressure distributions and distributions of stresses and strains in human body, as well as their impact to human psychological sensory perceptions. The CAD system is applied to establish scientific principles and framework for biomechanical engineering of biofunctional textile products to meet the requirements of biomedical and healthcare applications. Clothing biomechanical engineering design is a complex iterative-decision-making process. To increase efficiency in this complex process, an integration CAD system has been developed to provide an integrated environment from functional specification, data management, biomechanical computational simulation, design visualization and evaluation. To evaluate the pressure comfort performance of the design, a computational model has been developed to predict the mechanical sensory perception from skin pressure distributions, internal deformations, stresses and strains that are induced by the dynamic mechanical interactions between clothing and human body. To support designers and engineers to evaluate the biomechanical functional performances and sensory comfort of their design, visualization interfaces have been developed, which can not only present the quantitative data in scientific format, but also can transform the quantitative data to 3D color images to visually illustrate skin pressure distributions, deformations, stress and strain distributions in internal structure of the body, also create 3D color map to visualize the pressure sensory perceptions at different parts of the body. This integrated CAD system provides a technology platform for design and engineering of textiles and apparel products on the basis of scientific data with effective visual illustrations.
User Interface Management System with Geometric Modeling Capability: A CAD System's Framework
Authors: Tapio Takala
Venue: IEEE Computer Graphics and Applications (1985)

Since practical designing involves both ¿bottom-up¿ and ¿topdown¿ approaches, a CAD system should be able to cope with all types of data.
A Grouping Genetic Algorithm Using Linear Linkage Encoding for Bin Packing
Authors: Özgür Ülker, Emin Erkan Korkmaz, Ender Özcan
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

Linear Linkage Encoding (LLE) is a representation method proposed for grouping problems. It has already been used in solving data clustering, graph coloring and timetabling problems based on multi-objective genetic algorithms. In this study, this novel encoding scheme is investigated on bin packing again using a genetic algorithm. Bin packing benchmark problem instances are used to compare the performance of traditional recombination operators and custom made LLE crossover operators which are hybridized with parametrized placement heuristics. The results denote that LLE is a viable candidate for bin packing problem whenever appropriate genetic operators are chosen.
Model-Driven Adaptive Self-healing for Autonomic Computing
Authors: Yan Liu, Jing Zhang, John Strassner
Venue: Proceedings of the 3rd IEEE international workshop on Modelling Autonomic Communications Environments (2008)

Self-healing is a vital property that an autonomic system must possess in order to provide robust performance and survivability. The promise of self-healing depends on other properties that the system should provide, which include self-monitoring and self-configuring. Autonomic systems further require self-healing behavior to adapt to changes in user needs, business goals, and environmental conditions such that self-healing decisions are made dynamically and adaptively according to the system context. In this paper, we propose a model-driven approach that leverages modeling techniques, reliability engineering methodologies, and aspect-oriented development to realize an adaptive self- healing paradigm for autonomic computing.
Recent Advances in Photonic Devices for Optical Super Computing
Authors: Hossin Abdeldayem, Donald O. Frazier, William K. Witherow, Curtis E. Banks, Benjamin G. Penn, Mark S. Paley
Venue: Proceedings of the 1st international workshop on Optical SuperComputing (2008)

The twentieth century has been the era of semiconductor materials and electronic technology while this millennium is expected to be the age of photonic materials and optical technology. Optical technology has led to countless optical devices that have become indispensable in our daily lives in storage area networks (SANs) [1], parallel processing [2,3], optical switches [4,5], all-optical data networks [6], holographic storage devices [7] and biometric devices at airports [8].
Colorectal Polyps Detection Using Texture Features and Support Vector Machine
Authors: Da-Chuan Cheng, Wen-Chien Ting, Yung-Fu Chen, Qin Pu, Xiaoyi Jiang
Venue: Proceedings of the 3rd international conference on Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry (2008)

In this paper we propose a novel method in detecting colorectal polyps on colonoscopic images. Texture features are applied in polyps and normal tissues training and classification. Support vector machine is used as a classifier to identify the position of polyps. Seventy-four colonoscopic images are collected to test the system. Half of them are used as training images and half are used as testing. The experimental result shows the system can identify all polyps if the colonoscopic images contain single polyp. The sensitivity is 86.2% and the false-positive rate is 1.26 mark per-image.
Diversity-Based Feature Selection from Neural Network with Low Computational Cost
Authors: Md. Monirul Kabir, Md. Shahjahan, Kazuyuki Murase
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

This paper presents a new approach to identify the activity of input attributes efficiently in the wrapper model of feature selection. The relevant features are selected by the diversity among the inputs of the neural network and the entire process is done depending on several criteria. While the most of existing feature selection methods use all input attributes by examining network performance, we use here only the attributes having relatively high possibilities to contribute to the network performance knowing preceding assumptions. The proposed diversity-based feature selection method (DFSM) can therefore significantly reduce the size of hidden layer priori to feature selection process without degrading the network performance. We tested DFSM to several real world benchmark problems and the experimental results confirmed that it could select a small number of relevant features with good classification accuracies.
Programming the apocalypse: recombinant narrative in cyberspace
Authors: Stephen O'Leary
Venue:  (2007)

This study analyses the impact of the World Wide Web and digital technologies on the practice of apocalyptic rhetoric in cyberspace at beginning of the 21st century. As a mass medium and subset of the Internet, whose qualities include data exchangeability, nonlinear hyperlinking, and a relative lack of gatekeepers, the Web, the author contends, lends itself not only to more networked reasoning styles, but to mytho-logics. The Web as both a virtual repository for human knowledge and a universal publishing platform provides apocalyptically-minded individuals with the discursive power and resources to reason mythologically, programming synthetic fusions of mythos and logos in the creation of apocalyptic narratives drawn from a variety of traditions. Such &ldquo;recombinant narratives,&rdquo; the author finds, provide individuals with a sense of cosmic and personal meaning by acting as symbolic theodicies. Moreover, the author contends that the phenomena of data exchangeability, narrative programmability, and narrative syncretism are further evidenced in apocalyptically inflected neo-orthodoxies emerging on the Web which make apocalyptic scenarios intelligible in terms of digital technologies, even while denying or demonizing those same technologies.
Pervasive play, immersion and story: designing interference
Authors: John-Paul Bichard, Annika Waern
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

Pervasive games are games that are played in the real world---they are not played as a computerized simulation or on a limited physical game arena. The central attraction for pervasive games is that they offer the pleasure of doing things for real. The world is a vast and infinitely changing resource of content for pervasive games. Interference is a pervasive game playable by groups of 6--8 players lasting for a total of 3--4 hours and using both technology (such as GPS positioning and augmented reality) and human actors to create the full experience. In this paper, we describe the design goals for Interference and how these permeate through all aspects of the design of the game to create a coherent experience. Interference shows how an emotionally complex game experience can be achieved without resorting to ambiguity or deep role playing. The game has so far been staged on seven occasions and we briefly report on the experiences from those stagings.
Ontology: Use and Abuse
Authors: Simone Santini
Venue: Adaptive Multimedial Retrieval: Retrieval, User, and Semantics: 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007 Revised Selected Papers (2007)

This paper is a critical analysis of the use of ontology as an instrument to specify the semantics of a document. The paper argue that not only is a logic of the type used in ontology insufficient for such a purpose, but that the very idea that meaning is a property of a document that can be expressed and stored independently of the interpretation activity is misguided.The paper proposes, in very general lines, a possible alternative view of meaning as modification of context and shows that many current approaches to meaning, from ontology to emergent semantics, can be seen as spacial cases of this approach, and can be analyzed from a very general theoretical framework.
Second language learning in an online computer game: insights from theories of social interaction, practice, and nonlinear dynamics
Authors: Diane L. Schallert, Margaret A. Syverson
Venue:  (2007)

Research in second language acquisition has typically focused on classroom and laboratory settings. This study explores second language use in a non-classroom setting. It is based on research from divergent fields including theories of social interaction from sociology, theories of practice from anthropology, and nonlinear dynamics from the physical sciences. This study is a qualitative study, which employs both ethnographic and discourse analytic methods. The study examines native and non-native English speaker interactions on a MUD, a text-based online game. Data was collected for one year. The data for analysis consist primarily of logs of online interactions. The major conclusion of this study was that individuals acquire language appropriate to a particular environment by interacting with others in that environment. As individuals come to an environment and strive towards particular non-linguistic goals, they necessarily interact with others in the environment. As they do, they create shared ways of interacting. Through interaction, they refine the ways in which they speak. By employing multiple perspectives to guide the analysis, new insights into second language use and interaction can be obtained. This broadens our understanding of second language use in non-classroom settings. Implications for pedagogy in foreign language education are discussed.
Study on Relationship Between NIHSS and TCM-SSASD Based on the BP Neural Network Multiple Models Method
Authors: Zhang Yanxin, Xu Junfeng, Gao Ying, Hou Zhongsheng
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

In this paper, the complex nonlinear relationship between NIHSS and TCM-SSASD is analyzed. Much method based on the BP neural networks is induced to approximate this complex nonlinear relationship. At the same time, two schemes of multiple models are proposed to improve the approximation performance of the BP neural network. Through the comparison among these schemes, it is shown that there is exact complex nonlinear relationship between the two diagnosis sheets. The works in the paper would be guidance for the diagnosis of the Apoplexy Syndromes and assistant for the further study of the relation between Western medicine and Traditional Chinese Medicine.
Efficient nondestructive equality checking for trees and graphs
Authors: Michael D. Adams, R. Kent Dybvig
Venue: ACM SIGPLAN Notices (2008)

The Revised6 Report on Scheme requires its generic equivalence predicate, equal?, to terminate even on cyclic inputs. While the terminating equal? can be implemented via a DFA-equivalence or union-find algorithm, these algorithms usually require an additional pointer to be stored in each object, are not suitable for multithreaded code due to their destructive nature, and may be unacceptably slow for the small acyclic values that are the most likely inputs to the predicate. This paper presents a variant of the union-find algorithm for equal? that addresses these issues. It performs well on large and small, cyclic and acyclic inputs by interleaving a low-overhead algorithm that terminates only for acyclic inputs with a more general algorithm that handles cyclic inputs. The algorithm terminates for all inputs while never being more than a small factor slower than whichever of the acyclic or union-find algorithms would have been faster. Several intermediate algorithms are also presented, each of which might be suitable for use in a particular application, though only the final algorithm is suitable for use in a library procedure, like equal?, that must work acceptably well for all inputs.
A Flow Deviation Algorithm for Joint Optimization of Unicast and Anycast Flows in Connection-Oriented Networks
Authors: Krzysztof Walkowiak
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Our discussion in this article centers around a new heuristic algorithm based on Flow Deviation (FD) method deployed for joint optimization of unicast and anycast flows in connection-oriented networks. The optimization problem is NP-complete. Anycast is a one-to-one-of-many technique to deliver a packet to one of many hosts. Current computer networks convey mostly unicast traffic. However, the quantity of anycast traffic will grow in near future, since many new services that can use anycast paradigm are developed, e.g. peer-to-peer networks, content delivery networks, sensor networks, etc. In this work we focus on connection-oriented networks, in view of the fact that many transport networks are based on technologies like MPLS, GMPLS, and DWDM. Results of numerical experiments that compare performance of our approach against other heuristics are presented and discussed.
A CAD System for Long-Bone Segmentation and Fracture Detection
Authors: Martin Donnelley, Greg Knowles, Trevor Hearn
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

Medical imaging has advanced at a tremendous rate since x-rays were discovered in 1895. Today, x-ray machines produce extremely high-quality images for radiologists to interpret. However, the methods of interpretation have only recently begun to be augmented by advances in computer technology. Computer aided diagnosis (CAD) systems that guide healthcare professionals in making the correct diagnosis are slowly becoming more prevalent throughout the medical field. Detection of long-bone fractures is an important orthopaedic and radiologic problem, and it is proposed that a novel CAD system could help reduce the number of fractures missed during x-ray diagnosis. A number of image processing software algorithms useful for assisting the fracture detection process are described, and their accuracy evaluated on a database of fracture images from trauma patients. Incorporating these methods will further expand the capabilities of today's CAD systems, and result in more accurate diagnosis of fractures and a reduction of the fracture miss rate.
Grammar-Guided Neural Architecture Evolution
Authors: Jorge Couchet, Daniel Manrique, Luis Porras
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

This article proposes a context-free grammar to be used in grammar-guided genetic programming systems to automatically design feed-forward neural architectures. This grammar has three important features. The sentences that belong to the grammar are binary strings that directly encode all the valid neural architectures only. This rules out the appearance of illegal points in the search space. Second, the grammar has the property of being ambiguous and semantically redundant. Therefore, there are alternative ways of reaching the optimum. Third, the grammar starts by generating small networks. This way it can efficiently adapt to the complexity of the problem to be solved. From the results, it is clear that these three properties are beneficial to the convergence process of the grammar-guided genetic programming system.
Dynamic Partial Order Reduction Using Probe Sets
Authors: Harmen Kastenberg, Arend Rensink
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

We present an algorithm for partial order reduction in the context of a countable universe of deterministic actions, of which finitely many are enabled at any given state. This means that the algorithm is suited for a setting in which resources, such as processes or objects, are dynamically created and destroyed, without an a priori bound. The algorithm relies on abstract enabling and disabling relations among actions, rather than associated sets of concurrent processes. It works by selecting so-called probe sets at every state, and backtracking in case the probe is later discovered to have missed some possible continuation.We show that this improves the potential reduction with respect to persistent sets. We then instantiate the framework by assuming that states are essentially sets of entities (out of a countable universe) and actions test, delete and create such entities. Typical examples of systems that can be captured in this way are Petri nets and (more generally) graph transformation systems. We show that all the steps of the algorithm, including the estimation of the missed actions, can be effectively implemented for this setting.