ppxscal/embedding_network huggingface dataset:
An Ingenious, Piecewise Linear Interpolation Algorithm for Pricing Arithmetic Average Options
Authors: Tian-Shyr Dai, Jr-Yan Wang, Hui-Shan Wei
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

Pricing arithmetic average options continues to intrigue researchers in the field of financial engineering. Since there is no analytical solution for this problem until present, developing an efficient numerical algorithm becomes a promising alternative. One of the most famous numerical algorithms for pricing arithmetic average options is introduced by Hull and White [10]. In this paper, motivated by the common idea of reducing the nonlinearity error in the adaptive mesh model [7] and the adaptive quadrature numerical integration method [6], the logarithmically equally-spaced placement rule in the Hull and White's model is replaced by an adaptive placement method, in which the number of representative average prices is proportional to the degree of curvature of the option value as a function of the arithmetic average price. Numerical experiments verify the superior performance of our method in terms of reducing the interpolation error. In fact, it is straightforward to apply this method to any pricing algorithm with the techniques of augmented state variables and the piece-wise linear interpolation approximation.
Identifying Word Relations in Software: A Comparative Study of Semantic Similarity Tools
Authors: Giriprasad Sridhara, Emily Hill, Lori Pollock, K. Vijay-Shanker
Venue: Proceedings of the 2008 The 16th IEEE International Conference on Program Comprehension (2008)

Modern software systems are typically large and complex, making comprehension of these systems extremely difficult. Experienced programmers comprehend code by seamlessly processing synonyms and other word relations. Thus, we believe that automated comprehension and software tools can be significantly improved by leveraging word relations in software. In this paper, we perform a comparative study of six state of the art, English-based semantic similarity techniques and evaluate their effectiveness on words from the comments and identifiers in software. Our results suggest that applying English-based semantic similarity techniques to software without any customization could be detrimental to the performance of the client software tools. We propose strategies to customize the existing semantic similarity techniques to software, and describe how various program comprehension tools can benefit from word relation information.
Audio-Visual Clustering for 3D Speaker Localization
Authors: Vasil Khalidov, Florence Forbes, Miles Hansard, Elise Arnaud, Radu Horaud
Venue: Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction (2008)

We address the issue of localizing individuals in a scene that contains several people engaged in a multiple-speaker conversation. We use a human-like configuration of sensors (binaural and binocular) to gather both auditory and visual observations. We show that the localization problem can be recast as the task of clustering the audio-visual observations into coherent groups. We propose a probabilistic generative model that captures the relations between audio and visual observations. This model maps the data to a representation of the common 3D scene-space, via a pair of Gaussian mixture models. Inference is performed by a version of the Expectation Maximization algorithm, which provides cooperative estimates of both the activity (speaking or not) and the 3D position of each speaker.
Fractal Fault Diagnosis of Rotor System Based on Morphological De-nosing
Authors: Bi-qiang Du, Gui-ji Tang, Song-ling Wang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

As an experimental tool for analyzing movement of chaos, we intend to introduce the correlation dimension for analyzing vibration signals of rotor system in this paper. For noise corruption existing in field-measured vibration signal, morphological filter is also introduced for de-noising the vibration signal. The analysis and comparison between the correlation dimensions of the noised and de-noised vibration signals of rotor system at different states are done. The result shows that reflecting the system's characteristic with the correlation dimension of noised signal is largely unreliable, so the field-measured signal must be de-noised prior to the correlation dimension calculation. The favorable de-noising effect by morphological filter is also showed. The correlation dimension of de-noised vibration signals can reflect and distinguish the actual state of rotor effectively. As a character to classify the fault type and state of rotor in fault diagnosis, the correlation dimension after de-noising is feasible.
MIRACLE Progress in Monolingual Information Retrieval at Ad-Hoc CLEF 2007
Authors: José-Carlos González-Cristóbal, José Miguel Goñi-Menoyo, Julio Villena-Román, Sara Lana-Serrano
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper presents the 2007 MIRACLE's team approach to the AdHoc Information Retrieval track. The main work carried out for this campaign has been around monolingual experiments, in the standard and in the robust tracks. The most important contributions have been the general introduction of automatic named-entities extraction and the use of wikipedia resources. For the 2007 campaign, runs were submitted for the following languages and tracks: a) Monolingual: Bulgarian, Hungarian, and Czech. b) Robust monolingual: French, English and Portuguese.
Self-Protecting Session Initiation Protocol Stack
Authors: Zoran Rusinovic, Nikola Bogunovic
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

We present the Self-Protecting Session Initiation Protocol Stack capable of recognizing malicious SIP messages and protecting itself in high-load conditions. The stack model is based on the two-step processing and uses hash lookup tables and cellular automata rules to identify SIP message either as a regular or malicious one. Results show that a presented SIP stack exhibits very promising results with respect to messages classification and enables regular operation of SIP stack under high-load consisting of highly malicious traffic.
Dynamic Probabilistic Packet Marking with Partial Non-Preemption
Authors: Wei Yen, Jeng-Shian Sung
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

This paper studies the technique of probabilistic packet marking. The main purpose is for the receiver to trace the true sources of the marked packets and rebuild their paths rapidly. In many existing schemes, marked packets are overwritten by other marking routers because of the nature of probabilistic packet marking. Although some IP traceback schemes can improve the overwriting problem, they usually make unrealistic assumption[11] or do not consider the load balancing issue of the routers. In probabilistic packet marking, how to address the re-mark problem and how to balance routers' overhead are two important design considerations. A scheme is proposed in this paper to address these problems in probabilistic packet marking. Using computer simulation, we observe that our scheme can greatly reduce re-marking. When compared with the current IP traceback schemes, our scheme can reduce 65% marked packets than the other scheme. Moreover, the overhead of marking packet in each router is even out in the proposed scheme than the other.
Visualization of Secondary Flow Choking Phenomena in a Supersonic Air Ejector
Authors: P. Desevaux, A. Mellal, Y. Alves de Sousa
Venue: Journal of Visualization (2004)

The present study deals with the visualization of the air flow inside a supersonic ejector. Our attention is more precisely focused on the choked flow phenomenon which occurs along the mixing chamber of the secondary nozzle and which can be visualized by CFD. Laser tomography visualizations are used to validate the CFD model. The evolution of flow configuration in the ejector with the primary stagnation pressure is examined both in the case of zero secondary flow and in the case of free entrainment of induced air.
Adaptive fuzzy controller for nonlinear systems via genetic algorithm
Authors: P. C. Chen, W. L. Chiang, C. W. Chen, C. H. Tsai
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

In this paper, we describe a method of stability analysis for a GA-Based reference adaptive fuzzy sliding model controller for the handling of these problems for a nonlinear system. Firstly, an uncertain and nonlinear plant for the tracking of a reference trajectory is well approximated and described via a fuzzy model involving fuzzy logic control rules. Then, the initial values of the consequent parameter vector are decided via a genetic algorithm. Finally, an adaptive fuzzy sliding model controller is derived to simultaneously stabilize and control the system. The stability of the nonlinear system is ensured by the derivation of the stability criterion based upon Lyapunov's direct method.
Topic 10 Parallel Numerical Algorithms
Authors: Ian Duff, Michel Daydé, Matthias Bollhoefer, Anne Trefethen
Venue: Proceedings of the 13th European international conference on Parallel Processing (2007)

Efficient and robust parallel and distributed algorithms with portable and easy-to-use implementations for the solution of fundamental problems in numerical mathematics are essential components of most parallel software systems for scientific and engineering applications.
Automatic identification of weapons from images of the cartridge case head
Authors: Alejandro Legrä, Enrique Marañón, Hebert Pérez, Lisandro De La Torre, Arturo Quintana, Ricardo Quirós
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

This work is a preliminary step in the development of a computer system for automatic identification of weapons with the aid of fired cartridge cases. We study the particular characteristics that can be present on the bottom of the cartridge head, which are helpful for automatic identification of the corresponding weapon, and we discuss how to extract and use those features.
A Correlation-Based Distance Function for Nearest Neighbor Classification
Authors: Yanet Rodriguez, Bernard Baets, Maria M. Garcia, Carlos Morell, Ricardo Grau
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

The Nearest Neighbor rule is a well-known classification me-thod largely studied in the pattern recognition community, both for its simplicity and its performance. The definition of the distance function is central for obtaining a good accuracy on a given data set and different distance functions have been proposed to increase the performance. This paper proposes a new distance function based on the correlation of fuzzy sets, called Fuzzy Correlation-based Difference Metric. The proposed distance function is a generalization of the Value Difference Metric and applies to both nominal and continuous attributes in a uniform way. Fuzzy sets are used to represent numeric attributes. A uninorm operator is used to aggregate local differences. Experimental results using an standard $\mathit{k}$-NN algorithm show a significant improvement in comparison to other distance functions proposed before.
On-Line Learning Control for Discrete Nonlinear Systems Via an Improved ADDHP Method
Authors: Huaguang Zhang, Qinglai Wei, Derong Liu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper mainly discusses a generic scheme for on-line adaptive critic design for nonlinear system based on neural dynamic programming (NDP), more exactly, an improved action-depended dual heuristic dynamic programming (ADDHP) method. The principal merit of the proposed method is to avoid the model neural network which predicts the state of next time step, and only use current and previous states in the method, as makes the algorithm more suitable for real-time or on-line application for process control. In this paper, convergence proof of the method will also be given to guarantee the control to reach the optimal. At last, simulation result verifies the performance.
Probabilistic Planning in Hybrid Probabilistic Logic Programs
Authors: Emad Saad
Venue: Proceedings of the 1st international conference on Scalable Uncertainty Management (2007)

In this paper, we present a new approach to probabilistic planning based on logic programming, by relating probabilistic planning to hybrid probabilistic logic programs with probabilistic answer set semantics [32]. We show that any probabilistic planning problem, $\cal P$, can be translated into a hybrid probabilistic logic program whose probabilistic answer sets correspond to trajectories in $\cal P$, with associated probabilities. We formally prove the correctness of our approach. Moreover, we show that the complexity of finding a plan for a probabilistic planning problem in our approach is NP-complete. In addition, we show that any probabilistic planning problem, $\cal P$, can be encoded as a classical logic program with answer set semantics, whose answer sets corresponds to valid trajectories in $\cal P$. We also show that probabilistic planning problems can be encoded as proportional satisfiability problems.
Tagging municipality FAQs: a quest for interoperability
Authors: Yvonne Bjerke, Olov &#x00d6;stberg
Venue: AI Society (2008)

All organisations must be able to answer questions from their respective constituencies. It is not an exaggeration to say that, in this respect, it is a challenge to handle the extremely broad action platform of local government administrations (municipalities). The present paper is a walk-through of questions from the citizens that are managed at Botkyrka municipality, Sweden. It is focussed on the use of an &#x2018;intelligent&#x2019; citizen assistant.
Control Cases during the Software Development Life-Cycle
Authors: Joe Zou, Christopher J. Pavlovski
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

The control case is a tool that may be applied in software development to model non-functional requirements during the requirements engineering process. The control case complements the use case in requirements design by capturing the systems qualities not addressed by the use case. This includes attributes such as performance, security, and the prescribed technology and standards. Together, the use case and control case offer a more complete representation of the requirements that define the system to be developed. In this paper, we extend the previous work on the control case by illustrating how this modeling tool is applied during the software development lifecycle (SDLC) from initial requirements through to commercial deployment. This includes business process analysis, detailed requirements gathering, architecture & design, software build, systems testing, and deployment. This work helps to bridge the gap in applying the control case to model non-functional requirements, illustrating how control cases are decomposed and refined further during the SDLC.
Scanning integer matrices by means of two rectangular windows
Authors: Andrea Frosini, Maurice Nivat, Simone Rinaldi
Venue: Theoretical Computer Science (2008)

This paper deals with the reconstruction of integer matrices from rectangular scans. In particular, since the case of one rectangular scan has already been treated in a previous paper, we consider two rectangular scans, given as two integer matrices, and we investigate the existence and the possibility of reconstruction of a third binary matrix which is compatible with them. Furthermore, our inspection implies interesting side results about the number of these reconstructed matrices for different choices of the dimensions of two windows used in the input scans.
The Role of Service Granularity in a Successful SOA Realization A Case Study
Authors: Naveen Kulkarni, Vishal Dwivedi
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

This paper presents the case study of a leading US financial institution International Financial and Brokerage Services (IFBS), which faced SOA realization issues while it followed an inappropriate SOA design strategy. While riding on the SOA hype wave, it implemented thousands of fine grained web-services without paying much heed to issues like governance, and usage within its business processes. IFBS’s service portfolio comprises of a gamut of services which although on paper looked good, but presented a lot of challenges in their usage and maintenance. We address some of these issues in this paper and present our framework for SOA adoption (called INSOAP) which can be effective in a similar end- to-end SOA adoption exercise in an enterprise.
MINI: Mining Informative Non-redundant Itemsets
Authors: Arianna Gallo, Tijl Bie, Nello Cristianini
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Frequent itemset mining assists the data mining practitioner in searching for strongly associated items (and transactions) in large transaction databases. Since the number of frequent itemsets is usually extremely large and unmanageable for a human user, recent works have sought to define condensed representations of them, e.g. closed or maximal frequent itemsets. We argue that not only these methods often still fall short in sufficiently reducing of the output size, but they also output many redundant itemsets. In this paper we propose a philosophically new approach that resolves both these issues in a computationally tractable way. We present and empirically validate a statistically founded approach called MINI, to compress the set of frequent itemsets down to a list of informative and non-redundant itemsets.
Wavelet Analysis of Pulses in the Fitzhugh Model
Authors: Carlo Cattani, Massimo Scalia
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

The nonlinear dynamical system which models the axon impulse activity is studied through the analysis of the wavelet coefficients. A system with a high pulse source is analyzed in dependence of the amplitude. It is shown that there exists a critical value of the amplitude, and a catastrophe above it. This value is easily detected by the large values of the wavelet coefficients.
Anticipation and Believability
Authors: Carlos Martinho, Ana Paiva
Venue: The Challenge of Anticipation: A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems (2008)

In this chapter, we discuss the relation between anticipation and believability. We start by introducing the concept of believability and the importance of both emotion and anticipation in the generation of believable behaviour. Then, we present some related work examplifying how emotions and anticipation have been used in the field of synthetic characters, with a particular focus on anticipation. Afterwards, we present how the relation between anticipation and emotion has been researched by the authors to create the emotivector, an anticipatory mechanism aimed at assisting the generation of autonomous believable behaviour for synthetic characters. As a fusion between the fields of affective computing and anticipatory computing, the emotivector generates affective signals from the mismatch between predicted and sensed values, and is inspired by the psychology of emotion and attention. We present two applications of the emotivector, demonstrating its adequacy: one in the realtime control of a situated, embodied agent inhabiting a virtual world, and another, in the real-time control of the affective expressions of a robotic affective chess `buddy'. Finally, we describe a successful integration of the low-level emotivector mechanism in a high-level cognitive agent architecture and the benefits of such integration.
Automatic Inference of Upper Bounds for Recurrence Relations in Cost Analysis
Authors: Elvira Albert, Puri Arenas, Samir Genaim, Germán Puebla
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

The classical approach to automatic cost analysis consists of two phases. Given a program and some measure of cost, we first produce recurrence relations (RRs) which capture the cost of our program in terms of the size of its input data. Second, we convert such RRs into closed form (i.e., without recurrences). Whereas the first phase has received considerable attention, with a number of cost analyses available for a variety of programming languages, the second phase has received comparatively little attention. In this paper we first study the features of RRs generated by automatic cost analysis and discuss why existing computer algebra systems are not appropriate for automatically obtaining closed form solutions nor upper bounds of them. Then we present, to our knowledge, the first practical framework for the fully automatic generation of reasonably accurate upper bounds of RRs originating from cost analysis of a wide range of programs. It is based on the inference of ranking functions and loop invariants and on partial evaluation.
A Needed Rewriting Strategy for Data-Structures with Pointers
Authors: Rachid Echahed, Nicolas Peltier
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

We propose a reduction strategy for systems of rewrite rules operating on term-graphs. These term-graphs are intended to encode pointer-based data-structures that are commonly used in programming, with cycles and sharing. We show that this reduction strategy is optimal w.r.t. a given dependency schema, which intuitively encodes the "interferences" among the nodes in the term-graphs. We provide a new way of computing such dependency schemata.
2D & 3D Shepp-Logan Phantom Standards for MRI
Authors: H. Michael Gach, Costin Tanase, Fernando Boada
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

The Shepp-Logan phantom was created as a standard for computerized tomography (CT) image reconstruction simulations of the head. The phantom is also used frequently for magnetic resonance image (MRI) reconstruction and k-space simulations. However, while the CT version incorporated the radiation attenuation properties of the head and brain, the MRI version of the phantom was neither adapted to MR physics nor defined as a viable standard. As a result, it is not currently possible to compare and validate MR simulations from different research studies. In this paper, we present 2D and 3D Shepp-Logan MRI phantom standards and their analytic k-space representations based on existing CT standards after modification for MR physics. The standard includes T1 and T2 relaxation times for different fields strengths based on current literature.