ppxscal/embedding_network huggingface dataset:
A self-adaptable query allocation framework for distributed information systems
Authors: Jorge-Arnulfo Quiané-Ruiz, Philippe Lamarre, Patrick Valduriez
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2009)

In large-scale distributed information systems, where participants are autonomous and have special interests for some queries, query allocation is a challenge. Much work in this context has focused on distributing queries among providers in a way that maximizes overall performance (typically throughput and response time). However, preserving the participants' interests is also important. In this paper, we make the following contributions. First, we provide a model to define the participants' perception of the system regarding their interests and propose measures to evaluate the quality of query allocation methods. Then, we propose a framework for query allocation called Satisfaction-based Query Load Balancing (SQLB, for short), which dynamically trades consumers' interests for providers' interests based on their satisfaction. Finally, we compare SQLB, through experimentation, with two important baseline query allocation methods, namely Capacity based and Mariposa-like. The results demonstrate that SQLB yields high efficiency while satisfying the participants' interests and significantly outperforms the baseline methods.
A new framework for analyzing political news
Authors: Rodrigo Sandoval-Almazan, Sehl Mellouli, Faouzi Bouslama
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

In this paper, we describe the preliminary steps of a research idea to improve the information retrieval of political news, in order to manage and personalize political news for citizens and politicians. Using a program algorithm with some ontology, we propose a future study of political news taking in consideration the Mexican Case. This poster presents the problem, describes the algorithm functions and designs the study case for measuring Mexican political news in the forthcoming midterm election. Finally, we address some possible conclusions and future research
How did the e-learning session go? The Student Inspector
Authors: Oliver Scheuer, Claus Zinn
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Good teachers know their students, and exploit this knowledge to adapt or optimise their instruction. Traditional teachers know their students because they interact with them face-to-face in classroom or one-to-one tutoring sessions. In these settings, they can build student models, i.e., by exploiting the multi-faceted nature of human-human communication. In distance-learning contexts, teacher and student have to cope with the lack of such direct interaction, and this must have detrimental effects for both teacher and student. In a past study we have analysed teacher requirements for tracking student actions in computer-mediated settings. Given the results of this study, we have devised and implemented a tool that allows teachers to keep track of their learners' interaction in e-learning systems. We present the tool's functionality and user interfaces, and an evaluation of its usability.
Factored principal components analysis, with applications to face recognition
Authors: Ian L. Dryden, Li Bai, Christopher J. Brignell, Linlin Shen
Venue: Statistics and Computing (2009)

A dimension reduction technique is proposed for matrix data, with applications to face recognition from images. In particular, we propose a factored covariance model for the data under study, estimate the parameters using maximum likelihood, and then carry out eigendecompositions of the estimated covariance matrix. We call the resulting method factored principal components analysis. We also develop a method for classification using a likelihood ratio criterion, which has previously been used for evaluating the strength of forensic evidence. The methodology is illustrated with applications in face recognition.
Designing the 'record' button: using children's understanding of icons to inform the design of a musical interface
Authors: Lorna McKnight, Janet C. Read
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

While standard icons often exist for common tasks, it can be difficult to design meaningful icons for non-standard tasks. Following a desire to build a music application that does not rely on text-based instructions, this paper explores suitable iconic representations for a 'record music' function on a mobile device. A study was carried out with primary school children (aged 8--10) to explore their current understanding of icons and elicit their requirements. It was seen that they were familiar with common icons, but that audio recording remains a difficult concept to represent through icons alone.
Why are wordnets important?
Authors: Veronika Vincze, György Szarvas, János Csirik
Venue: Proceedings of the 2nd conference on European computing conference (2008)

Wordnets are lexical databases in which words are organized into clusters based on their meanings, and they are linked to each other through different semantic and lexical relations. The first wordnet called the Princeton WordNet was created for English, which were followed by various wordnets created within the framework of the EuroWordNet and BalkaNet projects, among others. Here we focus on the development of wordnets in general and of the Hungarian WordNet (HuWN). The process of constructing HuWn is illustrated by examples, some language-specific and language-independent problems encountered during the construction process are discussed, and then basic statistical data on HuWN are presented as well. Finally, two subontologies of HuWN, namely, the financial domain ontology and the legal domain ontology are also presented, and possible applications of WordNets are outlined.
SKIing with DOLCE: toward an e-Science Knowledge Infrastructure
Authors: Boyan Brodaric, Femke Reitsma, Yi Qiang
Venue: Proceeding of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008) (2008)

An ontology of general science knowledge (SKIo) is developed to enhance machine representation and use of scientific theories in emerging e-Science Knowledge Infrastructures. SKIo specializes the DOLCE foundational ontology with science knowledge primitives, such as science theory, model, data, prediction, and induction. These are arranged to reflect the complex knowledge structures used in science, such as scientific ideas playing different roles within and between theories. SKIo is encoded with OWL-DL, uses the DOLCE Descriptions and Situations module, and provides defining conditions for its primitives to enable an extensible bridge between DOLCE and domain science ontologies. An application to environmental theories is demonstrated, and its utility to other natural sciences is promising.
Inference in multi-state survival data
Authors: Luis Meira-Machado, Carmen Cadarso-Suárez, Jacobo Uña-Álvarez
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

In longitudinal studies of disease, patients can experience several events through a follow-up period. In these studies, the sequentially ordered events (gap times) are often of interest. The events of concern may be of the same nature (e.g. cancer patients may experience recurrent disease episodes) or represent different states in the disease process (e.g. alive and disease-free, alive with recurrence and dead). If the events are of the same nature this are usually referred as recurrent event, whereas if they represent different states (i.e. multistate models) they are usually modelled thought their intensity functions. In this paper we present new estimators for several quantities in a three-state model. We present a simple estimator for the bivariate distribution function for censored gap times and estimators for the transition probabilities. Another major goal is to study the relationship between the different covariates and disease evolution. The proposed methods were applied to a database on breast cancer. Software (in R) implementing the methods proposed in this paper were developed by the authors.
The ethics of information transparency
Authors: Matteo Turilli, Luciano Floridi
Venue: Ethics and Information Technology (2009)

The paper investigates the ethics of information transparency (henceforth transparency). It argues that transparency is not an ethical principle in itself but a pro-ethical condition for enabling or impairing other ethical practices or principles. A new definition of transparency is offered in order to take into account the dynamics of information production and the differences between data and information. It is then argued that the proposed definition provides a better understanding of what sort of information should be disclosed and what sort of information should be used in order to implement and make effective the ethical practices and principles to which an organisation is committed. The concepts of "heterogeneous organisation" and "autonomous computational artefact" are further defined in order to clarify the ethical implications of the technology used in implementing information transparency. It is argued that explicit ethical designs, which describe how ethical principles are embedded into the practice of software design, would represent valuable information that could be disclosed by organisations in order to support their ethical standing.
Plenary lecture III: nonparametric estimation for control engineering
Authors: Piotr Kulczycki
Venue: Proceedings of the 4th WSEAS/IASME international conference on Dynamical systems and control (2008)

The subject of this lecture is the application of nonparametric estimation methods - in particular statistical kernel estimators - for control engineering. Such methods allow the useful characterization of probability distributions without arbitrary assumptions regarding their membership to a fixed class. A detailed description of the Bayes parameter estimation with asymmetrical polynomial loss function will be given, as will one for fault detection in dynamical systems as objects of automatic control, in the scope of detection, diagnosis and prognosis of malfunctions. To this aim the basics of data analysis and exploration tasks - identification of outliers, clustering, and classification - solved using uniform mathematical apparatus based on the kernel estimators methodology will also be considered. In every case the final result will be an algorithm ensuring that its practical implementation does not demand of the user detailed knowledge of the theoretical aspects, or laborious research and calculations.
Journal ranking based on social information
Authors: Jinlong Wang, Ke Gao, Yongli Ren, Gang Li
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

Recently, literature analysis has become a hot issue in academic studies. In order to quantify the importance of journals and provide researchers with target vehicles for their work, this poster proposes a novel approach based on the social information through considering the potential relationship between journals quality and authors' affiliation. Based on the formula proposed in this work, the importance of journals can be estimated and ranked.
Agreement spaces for counselor agents
Authors: C. Carrascosa, M. Rebollo
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

This paper presents a model of agreement context as an euclidean space that can be solved as a Constraint Satisfaction Problem. This will allow to have a mediator (Counselor Agent) that models the agreement as an space, checks the viability of the agreement as it is being built, and even gives some counsels about the agreement terms being formulated.
Effect of Ag micro-particles content on the mechanical strength of the interface formed between Sn-Zn binary solder and Au/Ni/Cu bond pads
Authors: S. K. Das, A. Sharif, Y. C. Chan, N. B. Wong, W. K. C. Yung
Venue: Microelectronic Engineering (2009)

In this study, addition of Ag micro-particles with a content in the range between 0 and 4wt.% to a Sn-Zn eutectic solder, were examined in order to understand the effect of Ag additions on the microstructural and mechanical properties as well as the thermal behavior of the composite solder formed. The shear strengths and the interfacial reactions of Sn-Zn micro-composite eutectic solders with Au/Ni/Cu ball grid array (BGA) pad metallizations were systematically investigated. Three distinct intermetallic compound (IMC) layers were formed at the solder interface of the Au/electrolytic Ni/Cu bond pads with the Sn-Zn composite alloys. The more Ag particles that were added to the Sn-Zn solder, the more Ag-Zn compound formed to thicken the uppermost IMC layer. The dissolved Ag-Zn IMCs formed in the bulk solder redeposited over the initially formed interfacial Au-Zn IMC layer, which prevented the whole IMC layer lifting-off from the pad surface. Cross-sectional studies of the interfaces were also conducted to correlate with the fracture surfaces.
Taiwan's challenges for significant international tourism market growth
Authors: Yau-Tzu Ma, Andrea Crestan
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

This paper examines the nature of the Taiwanese tourism environment in a time where local tourism industries face significant challenges to attract international tourists to Taiwan. Based on a literature review of tourism marketing strategies as well as the use of information technology in the travel industry, the Force Field Analysis is used to address the significant transformation of this industry in the past ten years and examine the competency of Taiwanese inbound tour operators with the help of the government, which is actively promoting the country within the international tourism market. Indeed, the Force Field Analysis is a methodology that can be employed to examine tourism market evolution in the region as well as to identify the key forces driving and resisting the growth of the Taiwanese tourism industries in the international tourism market.
Elliptic Curve Cryptography with the TI-83
Authors: Blake Rice, Bill Yankosky
Venue: Cryptologia (2009)

It is possible to implement the ElGamal cryptosystem using elliptic curves over finite fields, thereby creating the potential for an extremely secure public-key cryptosystem. In this article, we show two things that may be somewhat surprising. First, the algorithms necessary to perform the computations required to generate elliptic curves over finite fields can easily be programmed into a TI-83 graphics calculator. Second, other TI-83 programs can be written to aid in the implementation of basic elliptic curve cryptosystems.
Daileon: a tool for enabling domain annotations
Authors: José Roberto C. Perillo, Eduardo M. Guerra, Clovis T. Fernandes
Venue: Proceedings of the Workshop on AOP and Meta-Data for Software Evolution (2009)

Software developers currently understand that the real complexity in most applications lies in the problem domain the software is dealing with. The approach known as domain-driven design follows the premises that, for most software projects, the primary focus should be on the domain and domain logic, and that complex domain designs should be based on a model. For this type of project, the concept of domain annotations, which is a way to define annotations specifically for domain objects, can be applied. Currently, most part of metadata-based components still does not use this concept. This paper proposes two techniques for enabling the use of domain annotations in new frameworks and existing ones, and introduces the Daileon framework, which enables such development in Java-based applications.
Direct analysis of wave digital network of microstrip structure with step discontinuities
Authors: Biljana P. Stošic, Miodrag V. Gmitrovic
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

A microstrip structure, divided into cascade connection of uniform sections, can be efficiently modelled by wave digital network [4]-[7]. Appropriate choice of a section number in digital model of microstrip structures is very important because of direct influence on the sampling frequency of the digital model, and on accuracy of desired response. Also, effects of the identified step discontinuities have to be compensated. In this paper, a choice of minimal number of sections based on given relative error, and one wave digital element for the step discontinuity are presented. Verification of the obtained results is done on one example of lowpass filter.
Evolutionary algorithm-based learning of fuzzy neural networks. Part 2: Recurrent fuzzy neural networks
Authors: R. A. Aliev, B. G. Guirimov, Bijan Fazlollahi, R. R. Aliev
Venue: Fuzzy Sets and Systems (2009)

Fuzzy neural networks (FNN) as opposed to neuro-fuzzy systems, whose main task is to process numerical relationships, can process both numerical (measurement based) information and perception based information. In spite of great importance of fuzzy feed-forward and recurrent neural networks for solving wide range of real-world problems, today there are no effective training algorithm for them. Currently there are two approaches for training of FNN. First approach is based on application of the level-sets of fuzzy numbers and the back-propagation (BP) algorithm. The second approach involves using evolutionary algorithms to minimize error function and determine the fuzzy connection weights and biases. The method based on the second approach was proposed by the authors and published in Part 1 of this paper [R.A. Aliev, B. Fazlollahi, R. Vahidov, Genetic algorithm-based learning of fuzzy neural networks. Part 1: feed-forward fuzzy neural networks, Fuzzy Sets and Systems 118 (2001) 351-358]. In contrast to the BP and other supervised learning algorithms, evolutionary algorithms do not require nor use information about differentials, and hence, they are most effective in case where the derivative is very difficult to obtain or even unavailable. However, the main deficiency of the existing FNN based on the feed-forward architecture is its adherence to static problems. In case of dynamic or temporal problems there is a need for recurrent fuzzy neural networks (RFNN). Designing efficient training algorithms for RFNN has recently become an active research direction. In this paper we propose an effective differential evolution optimization (DEO) based learning algorithm for RFNN with fuzzy inputs, fuzzy weights and biases, and fuzzy outputs. The effectiveness of the proposed method is illustrated through simulation of benchmark forecasting and identification problems and comparisons with the existing methods. The suggested approach has also been used for real applications in an oil refinery plant for petrol production forecasting.
A genetic_FPGA algorithm path planning of an autonomous mobile robot
Authors: Ouarda Hachour
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

This paper proposes Genetic Algorithms (GAs) for path Autonomous Mobile Robot (AMR). This approach has an advantage of adaptivity such that the GA works perfectly even if an environment is unknown. First, we present a software implementation GA path planning in a terrain. The results gotten of the GA on randomly generated terrains are very satisfactory and promising. Second, we discuss extensions of the GA for solving both paths planning and trajectory planning using a Single Static Random Access Memory (SRAM) for Field Programmable Gate Array (FPGA). This new design methodology based upon a VHDL description of the path planning has the two (02) advantages : to present a real autonomous task for mobile robots, and being generic and flexible and can be changed at the user demand. The results gotten are promising.
Malaysia IT outsourcing industry: practices, models, trends and challenges from a case of an offshore global service provider
Authors: Abdul Rahman Ahlan, Yusri Arshad, Mohd. Adam Suhaimi, Husnayati Hussin
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

Malaysia IT outsourcing (ITO) practices have been around after the Kodak effect but was not widely publicized until massive public sector computerization projects and automation of financial systems after Asian financial crisis in 1997. Thus, many service providers, including world-class firms, providing ITO business models can be found in operating in Malaysia. ITO models evolve from traditional to innovation phase in 2010 onwards. One of the innovative models in Malaysia is the global offshore service delivery model which is based on four pillars, namely: Experienced Leadership; Global Best Practice; Human Capital; Domain Knowledge. To be able to compete globally, Malaysia has equipped its companies with higher capabilities and competencies via international certifications and continuous skills developments. Several advantages proposed by Malaysia include: economic stability, political stability, multi-lingual, world-class infrastructure, affordable lifestyle, value propositions and many others. In this paper, we present the detailed views of a senior executive management on two open-ended in-depth interviews and one CEO roundtable discussion.
A Scalable and Adaptable Solution Framework within Components of the Community Climate System Model
Authors: Katherine J. Evans, Damian W. Rouson, Andrew G. Salinger, Mark A. Taylor, Wilbert Weijer, James B. White,  Iii
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

A framework for a fully implicit solution method is implemented into (1) the High Order Methods Modeling Environment (HOMME), which is a spectral element dynamical core option in the Community Atmosphere Model (CAM), and (2) the Parallel Ocean Program (POP) model of the global ocean. Both of these models are components of the Community Climate System Model (CCSM). HOMME is a development version of CAM and provides a scalable alternative when run with an explicit time integrator. However, it suffers the typical time step size limit to maintain stability. POP uses a time-split semi-implicit time integrator that allows larger time steps but less accuracy when used with scale interacting physics. A fully implicit solution framework allows larger time step sizes and additional climate analysis capability such as model steady state and spin-up efficiency gains without a loss in scalability. This framework is implemented into HOMME and POP using a new Fortran interface to the Trilinos solver library, ForTrilinos, which leverages several new capabilities in the current Fortran standard to maximize robustness and speed. The ForTrilinos solution template was also designed for interchangeability; other solution methods and capability improvements can be more easily implemented into the models as they are developed without severely interacting with the code structure. The utility of this approach is illustrated with a test case for each of the climate component models.