ppxscal/embedding_network huggingface dataset:
An Efficient Wavelet Based Feature Extraction Method for Face Recognition
Authors: Iman Makaremi, Majid Ahmadi
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

A computationally efficient wavelet based feature extraction method is proposed. This method is used for face recognition along with an HMM classifier. In comparison to similar method, this method needs less computation while the highest possible classification rate is still achievable. In this paper, different wavelet filters have been tried and effect of sub-image's size and overlap percentage in feature extraction on classification rate has been studied.
An automatic extraction method of word tendency judgement for specific subjects
Authors: Kazuhiro Morita, El-Sayed Atlam, Masao Fuketa, Yuya Iwabu, Jun-ichi Aoe
Venue: International Journal of Computer Applications in Technology (2009)

In recent years, there has been a tremendous growth of online text information related to digital libraries, medical diagnostic systems, remote education, news sources and electronic commerce. There is a great need to search and organise huge amount of information in text documents. This paper focuses on word tendencies in documents and presents an automatic extraction method for specific subject. Field judgment is conducted by using field association words and similarity among word tendencies, and other word tendencies are computed with information. Then word tendencies which have the same subject are grouped as one group and the important word tendencies are chosen from that group. Finally, a system suggests word tendencies from specific subjects and fields are implemented. From the experimental result, about 67&#37; of suggested word tendencies have been associated with popular subjects.
Motivationally Intelligent Systems: Diagnosis and Feedback
Authors: Benedict Du Boulay, Genaro Rebolledo Méndez, Rosemary Luckin, Erika Martínez-Mirón
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

: Motivationally intelligent systems deploy resources and tactics dynamically to maintain or increase the student's desire to learn and her willingness to expend effort in so doing. Three categories of diagnostic inputs and feedback reactions are outlined each with its associated meta-level. The meta-level includes the account which learners tell themselves, the system and others about what they know, how they feel, and the conditions under which they learn best.
A new visualization algorithm for the mandelbrot set
Authors: Raka Jovanovic, Milan Tuba, Dana Simian
Venue: Proceedings of the 10th WSEAS international conference on Mathematics and computers in biology and chemistry (2009)

In this paper we present a new method for displaying the Mandelbrot Set. Our algorithm is closely connected to Pickover Stalks and Buddhabrot method. Pickover Stalks method created biomorphs, diverse and complicated forms greatly resembling invertebrate organisms. Our method extends previously developed methods that preserve information about calculating the Mandelbrot Set. We observe the calculation-path of points tested for belonging to the Mandelbrot Set. Two variations of this display method are presented: one that only takes into account the paths taken and one that also uses information about their lengths.
Office 2007 in Easy Steps
Authors: Michael Price
Venue:  (2007)

Written for both new and experienced users, this handy guide concentrates on the most useful and productive elements of this essential software suite. It explains the applications included in the Standard edition Word, Excel, Outlook, PowerPoint, and Office Tools and also addresses other Office applications such as Access and Publisher. The applications are explained from the users point of view: what task the user wants to perform and what result the user wants to achieve. Among the topics covered are word processing, printing, calculations, presentations, financial statements, photo editing, slide shows, email, time management, creating databases, managing files and folders, and finding help. The commands and functions used to carry out tasks are explained in plain English through simple, clearly-defined steps that dont overwhelm the reader with confusing and unnecessary detail. 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
Nanosize copper dispersed ionic liquids as an electrolyte of new dye-sensitized solar cells
Authors: Fu-Lin Chen, I.-Wen Sun, H. Paul Wang, C.-H. Huang
Venue: Journal of Nanomaterials (2009)

To enhance the electrical conductivity of the electrolyte for a newly developed dye-sensitized solar cell (DSSC), metallic copper (Cu) encapsulated within the carbon shell (Cu@C) nanoparticles dispersed in a room temperature ionic liquid (RTIL) (e.g., [bmim+][PF6-]) has been studied in the present work. By the pulsed-field gradient spin-echo NMR method, the self-diffusion coefficients of cations and anions of the RTIL have been determined. The self-diffusion coefficient of the [bmim+] cations in the RTIL dispersed with 0.08% of Cu@C nanoparticles is increased by 35%. The electrical conductivity of the Cu@C dispersed RTIL is also increased by 65% (1.0 → 2.3ms/cm). It is very clear the nanosize Cu@C dispersed RTIL with a relatively greater diffusion coefficient and electrical conductivity can be a very effective electrolyte especially utilized in DSSCs.
Accurate Numerical Integration of Perturbed Oscillatory Systems in Two Frequencies
Authors: Fernando García-Alonso, José A. Reyes, José M. Ferrándiz, Jesús Vigo-Aguiar
Venue: ACM Transactions on Mathematical Software (TOMS) (2009)

Highly accurate long-term numerical integration of nearly oscillatory systems of ordinary differential equations (ODEs) is a common problem in astrodynamics. Scheifele&rsquo;s algorithm is one of the excellent integrators developed in the past years to take advantage of special transformations of variables such as the K-S set. It is based on using expansions in series of the so-called G-functions, and generalizes the Taylor series integrators but with the remarkable property of integrating without truncation error oscillations in one basic known frequency. A generalization of Scheifele&rsquo;s method capable of integrating exactly harmonic oscillations in two known frequencies is developed here, after introducing a two parametric family of analytical &phiv;-functions. Moreover, the local error contains the perturbation parameter as a factor when the algorithm is applied to perturbed problems. The good behavior and the long-term accuracy of the new method are shown through several examples, including systems with low- and high-frequency constituents and a perturbed satellite orbit. The new methods provide significantly higher accuracy and efficiency than a selection of well-reputed general-purpose integrators and even recent symplectic or symmetric integrators, whose good behavior in the long-term integration of the Kepler problem and the other oscillatory systems is well stated in recent literature.
Influence of the small arm barel boe length on the angle of jump dispresion
Authors: Roman Vítek
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

This article deals with an opportunity of the small arm fire accuracy improvement by choosing the proper ratio between the length of the guiding part of the bore and the overall length of the small arm barrel. The mathematical model of the flexural vibration of the small arm barrel is presented in this article and this model is used for determining of the correct bore/barrel length ratio. The derived mathematical model is verified erperimentally.
Combining Abduction with Conflict-based Diagnosis
Authors: Ildikó Flesch, Peter J. F. Lucas
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Conflict-based diagnosis is a recently proposed probabilistic method for model-based diagnosis, inspired by consistencybased diagnosis, that uses a measure of data conflict, called the diagnostic conflict measure, to rank diagnoses. In this paper, this method is refined using an abductive method that reuses part of the computation of the diagnostic conflict measure.
Modeling the Dynamics of Mood and Depression
Authors: Fiemke Both, Mark Hoogendoorn, Michel Klein, Jan Treur
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Both for developing human-like virtual agents and for developing intelligent systems that make use of knowledge about the emotional state of the user, it is important to model the mood of a person. In this paper, a model for simulating the dynamics of mood is presented, based on psychological theories about a uni-polar clinical depression. The model was analyzed mathematically and by means of simulations, and it was shown that the model exhibits the most important characteristics of the theories. It shows how stress factors under some conditions can lead to a depression, while it will not lead to a depression under other conditions.
Towards Social Dynamic Dependence Networks for Institutions
Authors: Serena Villata
Venue: Proceeding of the 2008 conference on STAIRS 2008: Proceedings of the Fourth Starting AI Researchers' Symposium (2008)

Social networks are structures that aim to represent the relationships among the actors of a society. In the multiagent model, these networks depict the dependencies among the agents. The dependencies reflect the relation between the goals of the agents and the agents who have the power to achieve them. Like any social structure, also a multiagent system can be regulated by a set of norms and institutional powers that form an institution. Differently than informal social networks, the institutional social structure has an inherent dynamic character which cannot be captured by the current dependence networks. The networks have to reflect the changes of dependencies among agents created by the exercise of institutional powers. The aim of this paper is to define more dynamic social networks. From a description of an agent system it is possible to build a static dependence network. In the same way we describe how to pass from an abstract representation of what is an institution with its institutional powers to a dynamic social dependence network.
Manufacturing Roadmaps as Information Modelling Tools in the Knowledge Economy
Authors: Augusta Maria Paci
Venue: Proceeding of the 2008 conference on Information Modelling and Knowledge Bases XIX (2008)

Roadmaps are the authorative medium-high tech viewpoints for the competitiveness and sustainability of industrial and public organizations. The paper provides an overview of possibilities to use roadmaps as virtual tools which contribute to support, coupled with knowledge management, industrial innovation and new industry processes. In the age of digitization, virtual roadmaps as a full participatory process supports new conceptual modelling of the manufacturing domain and at the same time it enables knowledge workers to share and elaborate innovative concepts. Hence roadmaps enable the design of new collaborative knowledge management environments. In medium time horizon, considering the global dimension of manufacturing, roadmaps can be reference tools for cooperation agreements in bilateral and multilateral projects. The paper provides a case study of roadmaps for advanced manufacturing and an example of the open innovation model.
An intelligent LED affective lighting system: a platform design for the realization of a user-centric affective life based on ISO/IEC 11179 in ubiquitous environments
Authors: Byounghee Son, Youngchoong Park
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

Recently, from device-centered automatic solutions, human emotion considered as an intelligent solution has been investigated. According to this idea, the importance of emotional technology has been raised. However, for investigating human emotion accurately, a technique that is able to recognize data comprehensively, including various and complex user context data, the condition of the user space, and changes to this space, are in demand. Additionally, research on sensors that can recognize various environments and studies of reasoning algorithms are necessary. In particular, research related to standard platforms and storage techniques for the recognition, reasoning, expression, and similar areas is necessary for extracting different personal attributes of variables such as gender, age, birth area, and race. Thus, the paper outlines the design of an intelligent LED affective lighting system that can determine the emotional condition of a user and supply light adequate to it after adaptively recognizing a user's physiological response as well as the space in which a user is active.
CTRNN Parameter Learning using Differential Evolution
Authors: Ivanoe De Falco, Antonio Della Cioppa, Francesco Donnarumma, Domenico Maisto, Roberto Prevete, Ernesto Tarantino
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Target behaviours can be achieved by finding suitable parameters for Continuous Time Recurrent Neural Networks (CTRNNs) used as agent control systems. Differential Evolution (DE) has been deployed to search parameter space of CTRNNs and overcome granularity, boundedness and blocking limitations. In this paper we provide initial support for DE in the context of two sample learning problems.
A New Method for Classifying Customer Purchasing Power
Authors: Junzhong Ji, Fan Chen, Chunnian Liu
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

Personalized recommendations in an intelligent B2C portal are an important topic in Web Intelligence. Aiming at identification of customer purchasing power, this paper proposes a classification method based on Ant Colony Optimization (ACO), in which an artificial ant constructs a classification rule in light of virtual pheromone associated with attribute-value pairs, then illustrates the method with a case study and discusses its application in personalized recommendation.
A unified framework for dynamic pari-mutuel information market design
Authors: Shipra Agrawal, Erick Delage, Mark Peters, Zizhuo Wang, Yinyu Ye
Venue: Proceedings of the tenth ACM conference on Electronic commerce (2009)

Recently, coinciding with and perhaps driving the increased popularity of prediction markets, several novel pari-mutuel mechanisms have been developed such as the logarithmic market scoring rule (LMSR), the cost-function formulation of market makers, and the sequential convex parimutuel mechanism (SCPM). In this work, we present a unified convex optimization framework which connects these seemingly unrelated models for centrally organizing contingent claims markets. The existing mechanisms can be expressed in our unified framework using classic utility functions. We also show that this framework is equivalent to a convex risk minimization model for the market maker. This facilitates a better understanding of the risk attitudes adopted by various mechanisms. The utility framework also leads to easy implementation since we can now find the useful cost function of a market maker in polynomial time through the solution of a simple convex optimization problem. In addition to unifying and explaining the existing mechanisms, we use the generalized framework to derive necessary and sufficient conditions for many desirable properties of a prediction market mechanism such as proper scoring, truthful bidding (in a myopic sense), efficient computation, controllable risk-measure, and guarantees on the worst-case loss. As a result, we develop the first proper, truthful, risk controlled, loss-bounded (in number of states) mechanism; none of the previously proposed mechanisms possessed all these properties simultaneously. Thus, our work could provide an effective tool for designing new market mechanisms.
Planning under temporal uncertainty indurative actions
Authors: J. Antonio Alvarez, Laura Sebastia, Eva Onaindia
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

Recently, planning under temporal uncertainty is becoming a very important and active field within the AI planning community. In this paper we present a new approach to handle planning problems with uncertain duration of actions. The novelty of this approach is that the management of the temporal uncertainty in durative actions is done independently of the planning process itself, which allows us to reduce the problem complexity. The experiments will show that we are able to obtain a plan that satisfies the user requirements for all the tested cases. Consequently, this work can be considered as a promising approach to handle this type of problems.
Complex flow simulations in natural aquifer
Authors: Hussein Mustapha
Venue: Advanced Engineering Informatics (2009)

Natural aquifers are complex media and contain heterogeneous structures. This paper introduces a new algorithm to simulate flow fluid in such complex media. A parallel version of the method is released, and two well-known sparse linear solvers, based, respectively, on a multifrontal Cholesky factorization and an iterative structured multigrid method, are tested. The mixed finite element (MFE) method is used to discretize Darcy's equation. The efficiency of the algorithm proposed is shown in different numerical examples.
Automatic refinement of an expressive speech corpus assembling subjective perception and automatic classification
Authors: Ignasi Iriondo, Santiago Planet, Joan-Claudi Socoró, Elisa Martínez, Francesc Alías, Carlos Monzo
Venue: Speech Communication (2009)

This paper presents an automatic system able to enhance expressiveness in speech corpora recorded from acted or stimulated speech. The system is trained with the results of a subjective evaluation carried out on a reduced set of the original corpus. Once the system has been trained, it is able to check the complete corpus and perform an automatic pruning of the unclear utterances, i.e. with expressive styles which are different from the intended corpus. The content which most closely matches the subjective classification remains in the resulting corpus. An expressive speech corpus in Spanish, designed and recorded for speech synthesis purposes, has been used to test the presented proposal. The automatic refinement has been applied to the whole corpus and the result has been validated with a second subjective test.
Performance Study of a Video Application over Multi Hop Wireless Networks with Statistic-Based Routing
Authors: Alexander Klein, Jirka Klaue
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

In recent years, technologies like Ultra Wideband (UWB) were developed that can be used to boost the data rate of wireless nodes to a new level. The higher data rate makes wireless networks capable of transporting multimedia content for real time applications like In Flight Entertainment (IFE), surveillance applications, or structural health monitoring. In this paper we measure and simulate the performance of a video application for IFE over a high data rate multi hop wireless network using a Directed Diffusion based routing protocol. Therefore, we take a look at the perceived video quality instead of focusing solely on the packet delivery ratio. Furthermore, we discuss the parameters of the Statistic-Based Routing (SBR) protocol which are relevant for this particular application and focus on their impact on the video quality during topology changes.
The Bounds on the Rate of Uniform Convergence of Learning Process on Uncertainty Space
Authors: Xiankun Zhang, Minghu Ha, Jing Wu, Chao Wang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Statistical Learning Theory on uncertainty space is investigated. The definitions of empirical risk functional, expected risk functional and empirical risk minimization principle on uncertainty space are introduced. Based on these concepts, the bounds on the rate of uniform convergence of learning process are given, which estimate the value of achieved risk for the function minimizing the empirical risk and the difference between the value of achieved risk and the value of minimal possible risk for a given set of functions.
A semantic framework for metamodel-based languages
Authors: Angelo Gargantini, Elvinia Riccobene, Patrizia Scandurra
Venue: Automated Software Engineering (2009)

In the model-based development context, metamodel-based languages are increasingly being defined and adopted either for general purposes or for specific domains of interest. However, meta-languages such as the MOF (Meta Object Facility)--combined with the OCL (Object Constraint Language) for expressing constraints--used to specify metamodels focus on structural and static semantics but have no built-in support for specifying behavioral semantics. This paper introduces a formal semantic framework for the definition of the semantics of metamodel-based languages. Using metamodelling principles, we propose several techniques, some based on the translational approach while others based on the weaving approach, all showing how the Abstract State Machine formal method can be integrated with current metamodel engineering environments to endow language metamodels with precise and executable semantics.We exemplify the use of our semantic framework by applying the proposed techniques to the OMG metamodelling framework for the behaviour specification of the Finite State Machines provided in terms of a metamodel.
Circuit and EM modeling of wideband high power VHF-UHF combiners
Authors: Song Lin, Aly E. Fathy, Gamal M. Hegazi, Thanh T. Chu
Venue: International Journal of RF and Microwave Computer-Aided Engineering (2009)

Design of wideband high power VHF-UHF combiners requires developing accurate equivalent circuit models. These high power combining structures generally use nonplanar lines and ferrite cores to enhance their power handling capabilities. For optimum and accurate design, part of these equivalent models should be based on full wave EM analysis. In this article, we present such detailed analysis and give examples for wideband isolating and nonisolating power combiners, along with a novel flux canceling circuitry that has been developed to potentially improve the intermodulation distortion performance of these power combiners. Good agreement between measured and simulated results has been successfully demonstrated for both designs with over 30&ndash;450 MHz bandwidth and less than half decibel insertion loss. &copy; 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.