ppxscal/embedding_network huggingface dataset:
Grey Relation Degree Analysis for the Facility's Location of Logistics Distribution Network
Authors: Bao Zhen-qiang, Wang Peng, Yang Fang, Zhu Cong-wei, Guo Lei
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

For the facility’s location of Logistics Distribution Network (LDN), we analyze a case that Wal-Mart chooses the logistics distribution centers in China. According to the candidate combination schemes and theirs criterions of the case, we retain the experts using Delphi method to get the weight distribution vectors of these schemes. Because analytic hierarchy process (AHP) method only uses the single criterion to compare but not takes the criterion relation into account. The criterions in facility’s location of Logistics Distribution network are not independence, the relation of the criterions are not clear but indeed. So, when we consider the location, we use the grey relation degree (GRD) method to compensate for the lack of AHP. And then we combine the GRD analysis to get the judgment matrix. Lastly, according to the weight distribution vector, we can get the integrative judgment result vector of the schemes and choose one with the maximum value as the optimal scheme.
A Simple and Efficient Fault-Tolerant Adaptive Routing Algorithm for Meshes
Authors: Arash Shamaei, Abbas Nayebi, Hamid Sarbazi-Azad
Venue: Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing (2008)

The planar-adaptive routing algorithm is a simple method to enhance wormhole routing algorithms for fault-tolerance in meshes but it cannot handle faults on the boundaries of mesh without excessive loss of performance. In this paper, we show that this algorithm can further be improved using a flag bit introduced for guiding misrouted messages. So, the proposed algorithm can be used to route messages when fault regions touch the boundaries of the mesh. We also show that our scheme does not lead to diminish the performance of the network and only three virtual channels per physical channels are sufficient for tolerating multiple boundary faulty regions.
Diffusional creep induced stress relaxation in thin Cu films on silicon
Authors: D. Chocyk, A. Proszynski, G. Gladyszewski
Venue: Microelectronic Engineering (2008)

The results of stress measurements during annealing of thin copper films deposited on 100@mm Si substrates are presented. The stress in thin films was determined by using an optical system for curvature measurements. The annealing experiments were done during thermal cycles of heating and cooling procedures from room temperature up to 400^oC with a rate 10^oC/min. The total thickness of thin films was between 20 and 100nm. The obtained results showed that the difference between the end and the initial values of the ratio of force to width increases with the thickness of the samples. The initial linear shape of the temperature-stress plots reaches higher temperature values with an increase in film thickness. In order to explain the observations, the dependence of stress on temperature was calculated using the rate of Coble creep. It was found that the theoretical curves reveal the same features as the experimental data. It was concluded that diffusional creep mechanism dominates for thin film of thickness below 100nm.
An Improved Algorithm for Estimating the ICA Model Concerning the Convergence Rate
Authors: Doru Constantin, Luminita State
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

The aim of the present paper is to propose a estimation algorithm of the ICA model, an algorithm based on successive approximations. The convergence rate of the successive approximations method are substantiated for the bidimensional case, a case which presents interest from a practical point of view, and we want to establish the performances of the proposed algorithm to estimate the independent components. Comparative analysis is done and experimentally derived conclusions on the performance of the proposed method are drawn in the last section of the paper for signals recognition applications.
Acoustic Modelling for Croatian Speech Recognition and Synthesis
Authors: Sanda Martinčić-Ipšić, Slobodan Ribarić, Ivo Ipšić
Venue: Informatica (2008)

This paper presents the Croatian context-dependent acoustic modelling used in speech recognition and in speech synthesis. The proposed acoustic model is based on context-dependent triphone hidden Markov models and Croatian phonetic rules. For speech recognition and speech synthesis system modelling and testing the Croatian speech corpus VEPRAD was used. The experiments have shown that Croatian speech corpus, Croatian phonetic rules and hidden Markov models as the modelling formalism can be used to develop speech recognition and speech synthesis systems in parallel for a highly flective and free order language like Croatian. We propose an evaluation procedure for speech synthesis, which combines an objective and a subjective evaluation approach and we present the achieved evaluation results. The proposed procedures for Croatian acoustic modelling were developed as parts of speech interfaces in a spoken dialog system for a limited weather forecast domain.
Understanding Mashup Development
Authors: Jin Yu, Boualem Benatallah, Fabio Casati, Florian Daniel
Venue: IEEE Internet Computing (2008)

Web mashups are Web applications developed using contents and services available online. Despite rapidly increasing interest in mashups over the past two years, comprehensive development tools and frameworks are lacking, and in most cases mashing up a new application implies a significant manual programming effort. This article overviews current tools, frameworks, and trends that aim to facilitate mashup development. The authors use a set of characteristic dimensions to highlight the strengths and weaknesses of some representative approaches.
A Functional Data Model Approach to Querying RDF/RDFS Data
Authors: João Martins, Rui Nunes, Merja Karjalainen, Graham J. Kemp
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

We are developing a multi-database architecture to provide integrated access to heterogeneous, distributed databases. The work described here is motivated by the desire to have RDF/RDFS collections as component data resources in this system, along with relational and other databases. To achieve this, the RDF/RDFS collection, like all other component resources in the system, is mapped to the functional data model, and a query translator is implemented that can translate queries originally expressed in Daplex (the query language associated with the functional data model) into SPARQL. SPARQL is the prominent query language for RDF and it is used here to bridge between the functional data model and the Semantic Web.
Multiple Modular Additions and Crossword Puzzle Attack on NLSv2
Authors: Joo Yeon Cho, Josef Pieprzyk
Venue: Proceedings of the 10th international conference on Information Security (2007)

NLS is a stream cipher which was submitted to the eSTREAM project. A linear distinguishing attack against NLS was presented by Cho and Pieprzyk, which was called Crossword Puzzle (CP) attack. NLSv2 is a tweak version of NLS which aims mainly at avoiding the CP attack. In this paper, a new distinguishing attack against NLSv2 is presented. The attack exploits high correlation amongst neighboring bits of the cipher. The paper first shows that the modular addition preserves pairwise correlations as demonstrated by existence of linear approximations with large biases. Next, it shows how to combine these results with the existence of high correlation between bits 29 and 30 of the S-box to obtain a distinguisher whose bias is around 2¿ 37. Consequently, we claim that NLSv2 is distinguishable from a random cipher after observing around 274 keystream words.
Verifying time, memory and communication bounds in systems of reasoning agents
Authors: Natasha Alechina, Brian Logan, Nguyen Hoang Nga, Abdur Rakib
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

We present a framework for verifying systems composed of heterogeneous reasoning agents, in which each agent may have differing knowledge and inferential capabilities, and where the resources each agent is prepared to commit to a goal (time, memory and communication bandwidth) are bounded. The framework allows us to investigate, for example, whether a goal can be achieved if a particular agent, perhaps possessing key information or inferential capabilities, is unable (or unwilling) to contribute more than a given portion of its available computational resources or bandwidth to the problem. We present a novel temporal epistemic logic, BMCL, which allows us to describe a set of reasoning agents with bounds on time, memory and the number of messages they can exchange. The bounds on memory and communication are expressed as axioms in the logic. As an example, we show how to axiomatize a system of agents which reason using resolution and prove that the resulting logic is sound and complete. We then show how to encode a simple system of reasoning agents specified in BMCL in the description language of a model checker, and verify that the agents can achieve a goal only if they are prepared to commit certain time, memory and communication resources.
Real-Time Gesture Recognition, Evaluation and Feed-Forward Correction of a Multimodal Tai-Chi Platform
Authors: Otniel Portillo-Rodriguez, Oscar O. Sandoval-Gonzalez, Emanuele Ruffaldi, Rosario Leonardi, Carlo Alberto Avizzano, Massimo Bergamasco
Venue: Proceedings of the 3rd international workshop on Haptic and Audio Interaction Design (2008)

This paper presents a multimodal system capable to understand and correct in real-time the movements of Tai-Chi students through the integration of audio-visual-tactile technologies. This platform acts like a virtual teacher that transfers the knowledge of five Tai-Chi movements using feed-back stimuli to compensate the errors committed by a user during the performance of the gesture. The fundamental components of this multimodal interface are the gesture recognition system (using k-means clustering, Probabilistic Neural Networks (PNN) and Finite State Machines (FSM)) and the real-time descriptor of motion which is used to compute and qualify the actual movements performed by the student respect to the movements performed by the master, obtaining several feedbacks and compensating this movement in real-time varying audio-visualtactile parameters of different devices. The experiments of this multimodal platform have confirmed that the quality of the movements performed by the students is improved significantly.
A Flexible Role- and Resource-Based Access Control Model
Authors: Yizhu Zhao, Yanhua Zhao, Hongwei Lu
Venue: Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 02 (2008)

RBAC realizes the separation of duty and helps to manage the users with various roles. However, RBAC cannot work well in distributed environment. In this paper, a flexible role- and resource- based access control model (called RRBAC) is proposed. RRBAC introduces role and resource concepts to access control, and provides a flexible approach for many security domains. RRBAC supports different types of resources sharing in open distributed environment. In the paper, we have a detailed description of RRBAC. Thereto, a use case is given to show how the model works, which illustrates that RRBAC is sound and reasonable.
Data Protection and Privacy Laws in the Light of RFID and Emerging Technologies
Authors: Gerald Quirchmayr, Christopher C. Wills
Venue: Proceedings of the 4th international conference on Trust, Privacy and Security in Digital Business (2007)

This paper investigates the effect of new technologies and new systems on data protection and privacy. It attempts to give an overview of the major issues resulting form the introduction of new systems, mainly those based on RFID and ubiquitous/pervasive computing technology and discusses the consequences of increased efficiency and improved security in relation to privacy protection. Most of the legally-oriented analysis carried out in this paper is primarily grounded in the current European data and privacy protection legislation.
Example-Based Learning for Single-Image Super-Resolution
Authors: Kwang In Kim, Younghee Kwon
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

This paper proposes a regression-based method for single-image super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underlying high-resolution image. A sparse solution of KRR is found by combining the ideas of kernel matching pursuit and gradient descent, which allows time-complexity to be kept to a moderate level. To resolve the problem of ringing artifacts occurring due to the regularization effect, the regression results are post-processed using a prior model of a generic image class. Experimental results demonstrate the effectiveness of the proposed method.
A Language Modeling Approach to Sentiment Analysis
Authors: Yi Hu, Ruzhan Lu, Xuening Li, Yuquan Chen, Jianyong Duan
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This paper presents a language modeling approach to the sentiment detection problem. It captures the subtle information in text processing to character the semantic orientation of documents as "thumb up" (positive) or "thumb down" (negative). To handle this problem, we propose an idea to estimate both the positive and negative language models from training collections. Tests are done through computing the Kullback-Leibler divergence between the language model estimated from test document and these two trained sentiment models. We assert the polarity of a test document by observing whether its language model is close to the trained "thumb up" model or the "thumb down" model. When compared with an outstanding classifier, i.e., SVMs on movie review corpus, language modeling approach showed its better performance.
Living Memory Annotation Tool --- Image Annotations for Digital Libraries
Authors: Wolfgang Jochum, Max Kaiser, Karin Schellner, Franz Wirl
Venue: Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries (2007)

Digital Libraries are currently discovering the full potential of web technologies in conjunction with building rich user communities and retaining customers. A visit to a digital library should nowadays offer more than passive consumption of content. Both the library and the user can benefit from moving forward from the "content provider" vs. "consumer" paradigm to the "prosumer" paradigm, thus allowing the user to produce and actively contribute content, interact with content and be part of communities of interest. We are presenting a smart annotation tool developed as part of the 'Living Memory' applications in the context of the EU-project BRICKS that supports the prosumer approach by inviting users to contribute new information by annotating content or commenting other annotations, thereby creating new knowledge in a collaborative way.
A robust spectral approach for blind watermarking of manifold surfaces
Authors: Yang Liu, Balakrishnan Prabhakaran, Xiaohu Guo
Venue: Proceedings of the 10th ACM workshop on Multimedia and security (2008)

This paper proposes a robust, blind, and imperceptible spectral watermarking approach for manifold surfaces represented as triangle meshes. The basic idea is to transform the original mesh into frequency domain using the Fourier-Like Manifold Harmonics Transform. The manifold harmonics basis defined on arbitrary topology surfaces is an intrinsic property of the manifold surfaces, i.e., it is only determined by the surface metric and independent of their resolution and embedding. This property makes our watermarking scheme immune to uniform affine attack (rotation, scaling, and translation) and robust against noise-addition and mesh simplification attacks. The global manifold harmonics are computed using the finite element method combined with a band-by-band algorithm that can compute thousands of eigenvectors for large meshes with up to a million triangles. The watermark data is embedded by modifying the manifold harmonics descriptors magnitude in an imperceptible way. By using global spectral analysis, the detection of such watermarks does not require mesh registration or re-sampling, and analysis of the statistics of the manifold harmonics descriptors is exploited to devise an optimal blind detector. Experimental results show the imperceptibility of the watermark with low distortions, and its robustness against the most common attacks including the uniform affine transformations, random noise addition, mesh simplification, etc.
Scalable isosurface visualization
Authors: Zhiyan Liu
Venue:  (2008)

Scientific data visualization assists users in understanding and analyzing large volumes of raw data by converting them into graphic representations. The main challenges in building a visualization system are large datasets, high-resolution displays, and the need to visualize remote datasets over slow networks. This dissertation focuses on visualizing isosurfaces efficiently under these challenges. First, to visualize large datasets efficiently on high-resolution displays, this dissertation proposes a new isosurface extraction algorithm that generates approximate results much faster than previous algorithms. The algorithm extracts portions of the isosurface in a view-dependent manner by ray casting and propagation. It casts rays through a volume to find visible active cells as seeds and then propagates their polygonal isosurface into the neighboring cells. Small pieces of the isosurface are generated by distance-limited propagation and joined together to form the final surface. Evaluation shows that this progressive algorithm generates an approximate result quickly before the final correct image is reached over time. In addition, the algorithm scales with the resolution of the display and supports adaptive-resolution visualization. This dissertation further discusses design options that are used for a fast implementation of the base algorithm. Finally, this dissertation presents a simple and effective protocol for remote isosurface visualization. The protocol breaks up the isosurface visualization pipeline at the 3D primitive stage for the server to send primitives to the client. Several techniques are introduced to reduce communication requirement and to provide interactive visualization. The server runs an efficient isosurface extraction algorithm that generates view-dependent portions of the isosurface. The resulting 3D primitives are organized into groups and sent to the client to be rendered. This approach uses primitive compression, progressive level-of-detail, and primitive caching techniques to improve the interactivity perceived by the user. This dissertation reports and compares the experiment results under different settings to show the effectiveness of these techniques. The results show that, when applied together, the techniques reduce both the amount of data transferred and time spent when the result becomes 90% correct by two orders of magnitude. 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
Random walks for feature-preserving mesh denoising
Authors: Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Frank C. Langbein
Venue: Computer Aided Geometric Design (2008)

An approach to mesh denoising based on the concept of random walks is examined. The proposed method consists of two stages: face normal filtering, followed by vertex position updating to integrate the denoised face normals in a least-squares manner. Face normal filtering is performed by weighted averaging of normals in a neighbourhood. A novel approach to determining weights is to compute the probability of arriving at each neighbour following a fixed-length random walk of a virtual particle starting at a given face of the mesh. The probability of the particle stepping from its current face to some neighbouring face is a function of the angle between the two face normals, based on a Gaussian distribution whose variance is adaptively adjusted to enhance the feature-preserving property of the algorithm. The vertex position updating procedure uses the conjugate gradient algorithm for speed of convergence. Analysis and experiments show that random walks of different step lengths yield similar denoising results. Our experiments show that, in fact, iterative application of a one-step random walk in a progressive manner effectively preserves detailed features while denoising the mesh very well. This approach is faster than many other feature-preserving mesh denoising algorithms.
Decompositions of Multiple Breakpoint Graphs and Rapid Exact Solutions to the Median Problem
Authors: Andrew Wei Xu, David Sankoff
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

The median genome problem reduces to a search for the vertex matching in the multiple breakpoint graph (MBG) that maximizes the number of alternating colour cycles formed with the matchings representing the given genomes. We describe a class of "adequate" subgraphs of MBGs that allow a decomposition of an MBG into smaller, more easily solved graphs. We enumerate all of these graphs up to a certain size and incorporate the search for them into an exhaustive algorithm for the median problem. This enables a dramatic speedup in most randomly generated instances with hundreds or even thousands of vertices, as long as the ratio of genome rearrangements to genome size is not too large.
Object-Oriented Software Systems Restructuring through Clustering
Authors: Gabriela Şerban, István-Gergely Czibula
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

It is well-known that maintenance and evolution represent important stages in the lifecycle of any software system (about 66% from the total cost of the software systems development). That is why in this paper we are focusing on the problem of automating an essential activity that appears in the maintenance and evolution of software systems: the problem of identifying refactorings that would improve the structure of the system. Refactoring is the process of improving the design of software systems, by improving their internal structure, without altering the external behavior of the code. The aim of this paper is to introduce a new clustering algorithm, CASYR (Clustering Algorithm for Software Systems Restructuring), that can be used for improving software systems design, by identifying the appropriate refactorings. The proposed approach can be useful for assisting software engineers in their daily work of refactoring software systems. We evaluate our approach on a real software system and we also provide a comparison with previous approaches.