ppxscal/embedding_network huggingface dataset:
Taylor series method with numerical derivatives for initial value problems
Authors: E. Miletics, G. Molnárka
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

The Taylor series method is one of the earliest analytic-numeric algorithms for approximate solution of initial value problems for ordinary differential equations. The main idea of the rehabilitation of these algorithms is based on the approximate calculation of higher derivatives using well-known technique for the partial differential equations. In some cases such algorithms will be much more complicated than a R-K methods, because it will require more function evaluation than well-known classical algorithms. However these evaluations can be accomplished fully parallel and the coefficients of truncated Taylor series can be calculated with matrix-vector operations. For large systems these operations suit for the parallel computers. The approximate solution is given as a piecewise polynomial function defined on the subintervals of the whole interval and the local error of this solution at the interior points of the subinterval is less than that one at the end point. This property offers different facility for adaptive error control. This paper describes several above-mentioned algorithms and examines its consistency and stability properties. It demonstrates some numerical test results for stiff systems herewith we attempt to prove the efficiency of these new-old algorithms.
Fuzzy control applied in prosthetics
Authors: Chivu Catrina, Chivu Catalin
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

Fuzzy controllers had a great development during last decades, and the applicability fields are increasing in number and variety. The present paper shows such a controller designed and applied for hand prosthesis. All the results presented in the paper were included in a large program, developed in Delphi language, program dedicated to hand prosthesis simulation.
Performance Assessment of HHT Marginal Spectrum Based on Resolution Measure
Authors: Ye Yuan, Wen-bo Mei, Si-liang Wu, Qi Yuan
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

This paper addresses the performance assessment of the marginal spectrum in Hilbert-Huang transform (HHT). We define a measure for assessing the resolution performance difference between HHT marginal spectrum and Fourier frequency spectrum instead of relying on visual inspection of its plot. The measure employs the key characteristics of spectrum, such as relative bandwidth for energy concentration measure about the signal frequency in the case of a single-tone signal, and the minimum frequency difference of two components for separation measure in the case of a composite two-tones signal. Numerical experiments show that the HHT marginal spectrum can increase not only the concentration the HHT marginal spectrum attains about the frequency components but the separation as well.
Multidimensional Blocking in UPC
Authors: Christopher Barton, Călin Caşcaval, George Almasi, Rahul Garg, José Nelson Amaral, Montse Farreras
Venue: Languages and Compilers for Parallel Computing: 20th International Workshop, LCPC 2007, Urbana, IL, USA, October 11-13, 2007, Revised Selected Papers (2007)

Partitioned Global Address Space (PGAS) languages offer an attractive, high-productivity programming model for programming large-scale parallel machines. PGAS languages, such as Unified Parallel C (UPC), combine the simplicity of shared-memory programming with the efficiency of the message-passing paradigm by allowing users control over the data layout. PGAS languages distinguish between private, shared-local, and shared-remote memory, with shared-remote accesses typically much more expensive than shared-local and private accesses, especially on distributed memory machines where shared-remote access implies communication over a network.In this paper we present a simple extension to the UPC language that allows the programmer to block shared arrays in multiple dimensions. We claim that this extension allows for better control of locality, and therefore performance, in the language.We describe an analysis that allows the compiler to distinguish between local shared array accesses and remote shared array accesses. Local shared array accesses are then transformed into direct memory accesses by the compiler, saving the overhead of a locality check at runtime. We present results to show that locality analysis is able to significantly reduce the number of shared accesses.
Approximate String Matching with Address Bit Errors
Authors: Amihood Amir, Yonatan Aumann, Oren Kapah, Avivit Levy, Ely Porat
Venue: Proceedings of the 19th annual symposium on Combinatorial Pattern Matching (2008)

A string S ¿ Σ m can be viewed as a set of pairs S = { (¿ i , i) : i ¿ { 0,..., m ¿ 1} }. We consider approximate pattern matching problems arising from the setting where errors are introduced to the location component (i), rather than the more traditional setting, where errors are introduced to the content itself (¿ i ). In this paper, we consider the case where bits of i may be erroneously flipped, either in a consistent or transient manner. We formally define the corresponding approximate pattern matching problems, and provide efficient algorithms for their resolution, while introducing some novel techniques.
Design and implementation of real-time fuzzy control for thermodynamic plant
Authors: Bilyana Tabakova
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

The paper presents the implementation of tuning techniques of single-input fuzzy logic controller (SIFLC) used for the control of a physical prototype of a thermodynamic plant. The idea behind such attempt is to analyze the practical consideration of the developed in MATLAB fuzzy control algorithms and to study their effectiveness in real time applications by a low-cost and time-saving manner. In the ground of such analysis is the estimation of the impact that the real environment may have on the designed by simulations control systems. The MATLAB based control algorithms which are implemented in this study are applied to the physical plant by data acquisition board (DAQ). Two basic tasks are fulfilled: 1) implementation of a SIFLC tuning algorithm based on a robust stability criterion in real-time control system; 2) analysis of the system performance and comparison of the results to ordinary PI control system and ordinary FLC system.
Reconstruction and Recognition of Occluded Facial Expressions Using PCA
Authors: Howard Towner, Mel Slater
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

Descriptions of three methods for reconstructing incomplete facial expressions using principal component analysis are given, projection to the model plane, single component projection and replacement by the conditional mean --- the facial expressions being represented by feature points. It is established that one method gives better reconstruction accuracy than the others. This method is used on a systematic reconstruction problem, the reconstruction of occluded top and bottom halves of faces. The results indicate that occluded-top expressions can be reconstructed with little loss of expression recognition --- occluded-bottom expressions are reconstructed less accurately but still give comparable performance to human rates of facial expression recognition.
Risk Analysis with Information Described in Natural Language
Authors: Chongfu Huang
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

In this paper, we give a new definition of risk: a scene in the future associated with some adverse incident. The simplest scene is that, a stone is hooked over our head. When a wind comes, the stone would fall down on our head. In many cases, what can we do is to approximately represent risks. In this paper, we suggest an approach to infer risks with information described in natural language. With fuzzy logic, we give a sample to verify that the suggested approach is more flexible and effective.
Pervasive Personalisation of Location Information: Personalised Context Ontology
Authors: William T. Niu, Judy Kay
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

There is considerable value in personalising information about people's location. Personalised Context Ontology (PECO) is an ontology for a building, and with PECO, we can provide personalised descriptions of the relevant people. For pragmatic reasons, it is important that PECO is created semi-automatically, making flexible use of a range of sources. For reasons of user control, it is important that PECO can be used to explain the personalisation. This paper describes PECO and how it is created for reasoning about a building. We also describe its use in an application called Locator, which presents information about the people in a building. PECO enables Locator to provide personalised information in two ways: it shows people of relevance and it makes use of personalised location labels. At the same time, PECO enables the user to scrutinise the reasoning about the personalisation. We report a study with eight users in which we compare a personalised and a non-adaptive versions of Locator. This indicates that people preferred the personalised version even though they could complete the designed tasks with both systems.
Hardware Acceleration for 3D Image Reconstruction
Authors: D. Chaikalis, G. Passalis, N. Sgouros, D. Maroulis, T. Theoharis
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

This work presents a hardware acceleration scheme for a 3D reconstruction method, targeting demanding dynamic Integral Imaging applications. The architecture exploits parallel processing and minimizes memory operations by implementing an efficient metric and an extended-access memory scheme. The employed data reutilization technique reduces overall throughput allowing the use of a single FPGA. Results reveal that the hardware system accelerates the software method by an order of magnitude and its processing rate surpasses the typical rate of a dynamic Integral Imaging acquisition system, making it suitable for robust 3D image and video reconstruction applications.
A Framework for Joint Cross-Layer and Node Location Optimization in Mobile Sensor Networks
Authors: Vladimir Marbukh, Kamran Sayrafian-Pour
Venue: Proceedings of the 7th international conference on Ad-hoc, Mobile and Wireless Networks (2008)

This paper proposes an extension to Network Utility Maximization (NUM) framework, referred to as L-NUM (Location-aware NUM). This framework is intended to characterize both the amount of the received sensor information and the network ability to deliver the information to the intended recipient(s). The sensor location is controlled by maximization of the system utility production, which accounts for both rate of the network utility increase and the negative effects of the energy consumption as a result of sensor motion. Definition of sensor utility in L-NUM incorporates the value of sensor information which is affected by sensor locations. Once model-specific network utility and system utility production are defined, L-NUM provides intuitively appealing and tractable framework for mobile sensor network optimization.
A memetic algorithm for the flexible flow line scheduling problem with processor blocking
Authors: Reza Tavakkoli-Moghaddam, Nima Safaei, Farrokh Sassani
Venue: Computers and Operations Research (2009)

This paper introduces an efficient memetic algorithm (MA) combined with a novel local search engine, namely, nested variable neighbourhood search (NVNS), to solve the flexible flow line scheduling problem with processor blocking (FFLB) and without intermediate buffers. A flexible flow line consists of several processing stages in series, with or without intermediate buffers, with each stage having one or more identical parallel processors. The line produces a number of different products, and each product must be processed by at most one processor in each stage. To obtain an optimal solution for this type of complex, large-sized problem in reasonable computational time using traditional approaches and optimization tools is extremely difficult. Our proposed MA employs a new representation, operators, and local search method to solve the above-mentioned problem. The computational results obtained in experiments demonstrate the efficiency of the proposed MA, which is significantly superior to the classical genetic algorithm (CGA) under the same conditions when the population size is increased in the CGA.
Robust Face Tracking Using Bilateral Filtering
Authors: Yoon-Hyung Lee, Mun-Ho Jeong, Joong-Jae Lee, Bum-Jae You
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

This paper introduces a method for face tracking in a video sequence in real time. In this method the profile of color distribution characterizes target's feature. It is invariant for rotation and scale changes. It's also robust to non-rigidity and partial occlusion of the target. We employ the mean-shift algorithm to track the target face and to reduce the computational cost. However, face tracking using color distribution is failed by noises as occlusion including some objects with similar color distribution and with exactly difference color distribution. Thus failures are critical problems. To solve these problems, we employ a bilateral filter which uses the color and range information. We have applied the proposed bilateral filter to track the real time face tracking. The experimental results demonstrate the efficiency of this algorithm. Its performance has been proven superior to the original mean shift tracking algorithm.
Advanced Tree-Based Kernels for Protein Classification
Authors: Elisa Cilia, Alessandro Moschitti
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

One of the aims of modern Bioinformatics is to discover the molecular mechanisms that rule the protein operation. This would allow us to understand the complex processes involved in living systems and possibly correct dysfunctions. The first step in this direction is the identification of the functional sites of proteins.In this paper, we propose new kernels for the automatic protein active site classification. In particular, we devise innovative attribute-value and tree substructure representations to model biological and spatial information of proteins in Support Vector Machines. We experimented with such models and the Protein Data Bank adequately pre-processed to make explicit the active site information. Our results show that structural kernels used in combination with polynomial kernels can be effectively applied to discriminate an active site from other regions of a protein. Such finding is very important since it firstly shows a successful identification of catalytic sites for a very large family of proteins belonging to a broad class of enzymes.
Regularization Versus Dimension Reduction, Which Is Better?
Authors: Yunfei Jiang, Ping Guo
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

There exist two main solutions for the classification of high-dimensional data with small number settings. One is to classify them directly in high-dimensional space with regularization methods, and the other is to reduce data dimension first, then classify them in feature space. However, which is better on earth? In this paper, the comparative studies for regularization and dimension reduction approaches are given with two typical sets of high-dimensional data from real world: Raman spectroscopy signals and stellar spectra data. Experimental results show that in most cases, the dimension reduction methods can obtain acceptable classification results, and cost less computation time. When the training sample number is insufficient and distribution is unbalance seriously, performance of some regularization approaches is better than those dimension reduction ones, but regularization methods cost more computation time.
A Jump Inversion Theorem for the Degree Spectra
Authors: Alexandra A. Soskova
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

A jump inversion theorem for the degree spectra is presented. For a structure which degree spectrum is a subset of the jump spectrum of a structure , a structure is constructed as a Marker's extension of such that the jump spectrum of is exactly the degree spectrum of and the degree spectrum of is a subset of the degree spectrum of .
Secure Password Authentication for Distributed Computing
Authors: Seung Wook Jung, Souhwan Jung
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

This paper describes secure password-based authentication involving a trusted third party, while the previous secure password authentication schemes focused on authentication involving two parties who shares the password. Kerberos is a well-known password-based authentication protocol involving a trusted third party. However, Kerberos is weak against the dictionary attack, suffers from a single point of failure. Additionally, Kerberos cannot provide a forward secrecy, which protects past sessions and further compromise, when a password is revealed. Our password authentication schemes provides Single Sign On like Kerberos and is secure against on/off-line dictionary attack. Moreover, The schemes provide a forward secrecy, and reduces the damage of the single point of failure.
A Survey on the Use of Mobile Phones by Visually Impaired Persons in Japan
Authors: Tetsuya Watanabe, Manabi Miyagi, Kazunori Minatani, Hideji Nagaoka
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

The present state and future needs of visually impaired mobile phone users were surveyed. The results showed that many visually impaired users, even print enabled persons, were making use of speech output to e-mail and to access the Internet, and, accordingly, improvements of speech output were requested. Additionally, GPS navigation was on the high priority request list.
A Generic Approach for Automatic Model Composition
Authors: Franck Fleurey, Benoit Baudry, Robert France, Sudipto Ghosh
Venue: Models in Software Engineering: Workshops and Symposia at MoDELS 2007, Nashville, TN, USA, September 30 - October 5, 2007, Reports and Revised Selected Papers (2008)

Analyzing and modelling a software system with separate views is a good practice to deal with complexity and maintainability. When adopting such a modular approach for modelling, it is necessary to have the ability to automatically compose models to build a global view of the system. In this paper we propose a generic framework for composition that is independent from a modelling language. We define a process for adapting this framework to particular modelling language (defined with a metamodel) and illustrate how the generic composition has been specialized for class diagrams.
Extraction of voltage harmonics using multi-layer perceptron neural network
Authors: Mehmet T&#x00fc;may, M. Emin Meral, K. &#x00c7;a&#x011f;atay Bayindir
Venue: Neural Computing and Applications (2008)

This paper presents a harmonic extraction algorithm using artificial neural networks for Dynamic Voltage Restorers (DVRs). The suggested algorithm employs a feed forward Multi Layer Perceptron (MLP) Neural Network with error back propagation learning to effectively track and extract the 3rd and 5th voltage harmonics. For this purpose, two different MLP neural network structures are constructed and their performances compared. The effects of hidden layer, supervisors and learning rate are also presented. The proposed MLP Neural Network algorithm is trained and tested in MATLAB program environment. The results show that MLP neural network enable to extract each harmonic effectively.
LHT: A Low-Maintenance Indexing Scheme over DHTs
Authors: Yuzhe Tang, Shuigeng Zhou
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

DHT is a widely-used building block in P2P systems, and complex queries are gaining popularity in P2P applications. To support efficient query processing over DHTs, effective indexing structures are essential. Recently, a number of indexing schemes have been proposed. However, these schemes have focused on improving query efficiency, and as a trade-off, sacrificed maintenance efficiency — an important performance measure in the P2P context, where frequent data updating and high peer dynamism are typically incurred. In this paper, we propose LHT, a Low maintenance Hash Tree, for efficient data indexing over DHTs. LHT employs a novel naming function and a tree summarization strategy to gracefully distribute its index structure. It is adaptable to any DHT substrates, and is easy to be implemented and deployed. Experiments show that in comparison with the state-of-the-art indexing technique, LHT saves up to 75% (at least 50%) maintenance cost, and achieves better performance for exact-match queries and range queries.
On the k-subgraphs of the generalized n-cubes
Authors: Geoffrey A. Solano, Jaime D. L. Caro
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

Graphs are used in modeling interconnections networks and measuring their properties. Knowing and understanding the graph theoretical/combinatorial properties of the underlying networks are necessary in developing more efficient parallel algorithms as well as fault-tolerant communication/routing algorithms [1]. The hypercube is one of the most versatile and efficient networks yet discovered for parallel computation. One generalization of the hypercube is the n-cube Q(n,m) which is a graph whose vertices are all the binary n- tuples, such that two vertices are adjacent whenever they differ in exactly m coordinates. The k-subgraph of the Generalized n-cube Qk(n,m) is the induced subgraph of the n-cube Q(n,m) where q=2, such that a vertex v ∈ V(Qk(n,m)) if and only if v ∈ V(Q(n,m)) and v is of parity k. This paper presents some degree properties of Qk(n,m) as well as some isomorphisms it has with other graphs, namely: 1) Qn-1 (n,2) is isomorphic to Kn 2) Qk(n,2i) is isomorphic to Gi(n,k) 3) QS(n,2i) is isomorphic to SGi(n).