ppxscal/embedding_network huggingface dataset:
Accurate instantaneous frequency estimation with iterated Hilbert transform and its application
Authors: Shuren Qin, Yi Qin, Yongfang Mao
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

Iterated Hilbert transform (IHT) is a new method for multicomponent demodulation. The principle of IHT is introduced, and some of its properties are researched. Although the amplitudes of the demodulated components obtained by IHT are accurate, there are limitations in the direct estimation of instantaneous frequencies via the extracted phases, so a smoothed instantaneous frequency estimation (SIFE) method based on difference operator and zero-phase digital low-pass filtering is proposed. The simulation results show that the proposed approach has higher performance than the adaptive segmentation algorithm and Hilbert-Huang transform. Finally, IHT and SIFE are applied to fault diagnosis of a rolling bearing, and the results show that the multicomponent fault vibration signal can be demodulated correctly and the weak feature of fault signals can be extracted efficiently with IHT and SIFE.
Knowledge Inferencing on Chinese Chess Endgames
Authors: Bo-Nian Chen, Pangfeng Liu, Shun-Chin Hsu, Tsan-Sheng Hsu
Venue: Proceedings of the 6th international conference on Computers and Games (2008)

Several Chinese chess programs exhibit grandmaster playing skills in the opening and middle game. However, in the endgame phase, the programs only apply ordinal search algorithms; hence, they usually cannot exchange pieces correctly. Some researchers use retrograde algorithms to solve endgames with a limited number of attack pieces, but this approach is often not practical in a real tournament. In a grandmaster game, the players typically perform a sequence of material exchanges between the middle game and the endgame, so computer programs can be useful. However, there are about 185 million possible combinations of material in Chinese chess, and many hard endgames are inconclusive even to human masters. To resolve this problem, we propose a novel strategy that applies a knowledge-inferencing algorithm on a sufficiently small database to determine whether endgames with a certain combination of material are advantageous to a player. Our experimental results show that the performance of the algorithm is good and reliable. Therefore, building a large knowledge database of material combinations is recommended.
Counting Finite Residuated Lattices
Authors: Radim Belohlavek, Vilem Vychodil
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

We study finite residuated lattices with up to 11 elements. We present an algorithm for generating all non-isomorphic finite residuated lattices with a given number of elements. Furthermore, we analyze selected properties of all the lattices generated by our algorithm and present summarizing statistics.
On model checking multiple hybrid views
Authors: Altaf Hussain, Michael Huth
Venue: Theoretical Computer Science (2008)

Many applications, for instance the MS .NET Global Assembly Cache (GAC), are naturally expressed as 3-valued models where an additional third truth value models uncertainty or under-specification. An example of under-specification is that a component in a GAC may or may not have a main method. Models described in this manner can then be analyzed to refute or verify properties about the concrete systems they intend to model. This approach to system validation traditionally considers only one model at a time, even though this model may evolve if subjected to analysis. Many applications, however, benefit from or require the simultaneous consideration of multiple models of systems. We mention here requirements from different stake holders, and data drawn from federated databases. This paper therefore builds the mathematical foundations for property verification and refutation as applied to finitely many 3-valued models, where each model is endowed with states - possibly named by nominals, also known as hybrid constraints - labelled transitions, and atomic propositions. Specifically, we show that deciding whether a finite set of models has a common concrete system (consistency) is typically in PTIME, and that deciding whether a common concrete system satisfies a formula of the hybrid mu-calculus (satisfiability), and its dual (validity), are EXPTIME-complete. We propose sound and efficient approximations of these EXPTIME-complete checks by synthesizing and checking ''summary'' models. These approximations are optimal if all models are deterministic. Finally, we point out that such optimality of summary models is unattainable whenever not all summarized models are deterministic.
Automatic Diagnosis of the Footprint Pathologies Based on Neural Networks
Authors: Marco Mora, Mary Carmen Jarur, Daniel Sbarbaro
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Currently foot pathologies, like cave and flat foot, are detected by an human expert who interprets a footprint image. The lack of trained personal to carry out massive first screening detection campaigns precludes the routinary diagnostic of these pathologies. This work presents a novel automatic system, based on Neural Networks (NN), for foot pathologies detection. In order to improve the efficiency of the neural network training algorithm, we propose the use of principal components analysis to reduce the number of inputs to the NN. The results obtained with this system demonstrate the feasibility of building automatic diagnosis systems based on the foot image. These systems are very valuable in remote areas and can be also used for massive first screening health campaigns.
VPDP: A Service Discovery Protocol for Ubiquitous Computing
Authors: Zhaomin Xu, Ming Cai, Jinxiang Dong
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Many service discovery protocols have been proposed by far to support ubiquitous computing. But they don't always apply to ubiquitous computing because of their confines. In this paper, we propose a service discovery protocol named VPDP adopted in our DOM-based middleware architecture, which aims to support as many types of ubiquitous environments as possible. VPDP is important for our middleware architecture to accommodate heterogeneity and uncertainty of ubiquitous computing environments.
Creating and Scripting Second Life Bots Using MPML3D
Authors: Birgit Endrass, Helmut Prendinger, Elisabeth André, Mitsuru Ishizuka
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

The use of virtual characters becomes invariably common in computer games and other applications. So-called "bots" (computer-controlled virtual characters), may explain virtual settings in a natural way. We describe an example scenario in the online world Second Life [1] in order to explain to content creators how to create bots and script their behavior using the well established authoring language MPML3D [2]. MPML3D does not assume knowledge of a high-level programming language. In Second Life users are represented by their avatars (virtual characters controlled by humans) and its environment provides character models, animations and a graphics engine.
Analysis of Software Functional Size Databases
Authors: Juan J. Cuadrado-Gallego, Miguel Garre, Ricardo J. Rejas, Miguel-Ángel Sicilia
Venue: Software Process and Product Measurement: International Conference, IWSM-Mensura 2007, Palma de Mallorca, Spain, November 5-8, 2007. Revised Papers (2007)

Parametric software effort estimation models rely on the availability of historical project databases from which estimation models are derived. In the case of large project databases with data coming from heterogeneous sources, a single mathematical model cannot properly capture the diverse nature of the projects under consideration. Clustering algorithms can be used to segment the project database, obtaining several segmented models. In this paper, a new tool is presented, Recursive Clustering Tool, which implements the EM algorithm to cluster the projects, and allows use different regression curves to fit the different segmented models. This different approaches will be compared to each other and with respect to the parametric model that is not segmented. The results allows conclude that depending on the arrangement and characteristics of the given clusters, one regression approach or another must be used,and in general, the segmented model improve the unsegmented one.
Inverse System Identification of Nonlinear Systems Using LSSVM Based on Clustering
Authors: Changyin Sun, Chaoxu Mu, Hua Liang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

In this paper we propose the algorithm of embedding fuzzy c-means (FCM) clustering in least square support vector machine (LSSVM). We adopt the method to identify the inverse system with immeasurable crucial variables and the inenarrable nonlinear character. In the course of identification, we construct the allied inverse system by the left inverse soft-sensing function and the right inverse system, and decide the number of clusters by a validity function, then utilize the proposed method to approach the nonlinear allied inverse system via offline training. Simulation experiments are performed and indicate that the proposed method is effective and provides satisfactory performance with excellent accuracy and low computational cost.
Matching slides to presentation videos
Authors: Kobus Barnard
Venue:  (2008)

Video streaming is becoming a major channel for distance learning (or e-learning). A tremendous number of videos for educational purpose are captured and archived in various e-learning systems today throughout schools, corporations and over the Internet. However, making information searchable and browsable, and presenting results optimally for a wide range of users and systems, remains a challenge. In this work two core algorithms have been developed to support effective browsing and searching of educational videos. The first is a fully automatic approach that recognizes slides in the video with high accuracy. Built upon SIFT (scale invariant feature transformation) keypoint matching using RANSAC (random sample consensus), the approach is independent of capture systems and can handle a variety of videos with different styles and plentiful ambiguities. In particular, we propose a multi-phase matching pipeline that incrementally identifies slides from the easy ones to the difficult ones. We achieve further robustness by using the matching confidence as part of a dynamic Hidden Markov model (HMM) that integrates temporal information, taking camera operations into account as well. The second algorithm locates slides in the video. We develop a non-linear optimization method (bundle adjustment) to accurately estimate the projective transformations (homographies) between slides and video frames. Different from estimating homography from a single image, our method solves a set of homographies jointly in a frame sequence that is related to a single slide. These two algorithms open up a series of possibilities for making the video content more searchable, browsable and understandable, thus greatly enriching the user's learning experience. Their usefulness has been demonstrated in the SLIC (Semantically Linking Instructional Content) system, which aims to turn simple video content into fully interactive learning experience for students and scholars.
The IT Infrastructure Library (ITIL) --- An Introduction for Practitioners and Researchers
Authors: Thomas Schaaf
Venue: Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management (2007)

The IT Infrastructure Library (ITIL) is a today widely-used collection of best practices in IT Service Management that has, of all standardization efforts, gained the biggest popularity. Since it combines the principles of service- and process-orientation in IT Management and is easily accessible, it has become increasingly attractive for IT organizations of almost any size, branch or organizational setup. The scope of ITIL is not limited to technical issues, but also covers the human and economic dimensions (business alignment) of IT Service Management.In this tutorial we give a survey on the ITIL framework structure and its most important concepts and contents, including an outline of five of ITIL's core reference processes. Furthermore, the tutorial discusses some important research topics related to ITIL, in particular Management Information Modelling and Tool Support. The five processes selected for presentation within the tutorial are Incident Management, Problem Management, Change Management, Configuration Management and Service Level Management. Learn how theses processes are designed and how they can be implemented.These topics include the exemplary consideration of an IT incident being recorded, classified and investigated, triggering Problem Management and passing Problem and Error Control before creating a Request for Change for the resolution of the incident and its underlying root cause. Learn how ITIL helps the IT organization to deal with unexpected events in a highly dynamic environment on the one hand, and how it supports the continuous improvement and strategic alignment of IT management. We show how the core processes correlate to each other and point out the central role of Configuration Management and the challenge of setting up a Configuration Management Database (CMDB). Find out what makes a CMDB setup so difficult, which requirements a CMDB should fulfill and why the current commercial and scientific efforts address these challenges insufficiently.Adequate tools are vital for a successful deployment of ITIL. But since ITIL is tool-independent and hardly formalized, sufficient and integrated tool support for ITIL is not available today. In the tutorial, we present a taxonomy for ITIL processes under tool support aspects by assessing each ITIL process as to its recurrence, lead time, organizational complexity, service level impact and structure.Finally, we show how ITIL emerged to the ISO/IEC 20000 standard and give an overview of the innovations expected for the next official release "ITIL V.3", scheduled for this year.
Proof Systems for Effectively Propositional Logic
Authors: Juan Antonio Navarro, Andrei Voronkov
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

We consider proof systems for effectively propositional logic. First, we show that propositional resolution for effectively propositional logic may have exponentially longer refutations than resolution for this logic. This shows that methods based on ground instantiation may be weaker than non-ground methods. Second, we introduce a generalisation rule for effectively propositional logic and show that resolution for this logic may have exponentially longer proofs than resolution with generalisation. We also discuss some related questions, such as sort assignments for generalisation.
The structure of decomposable indistinguishability operators
Authors: J. Recasens
Venue: Information Sciences: an International Journal (2008)

Decomposable fuzzy relations are studied. Symmetric fuzzy relations are proved to be generated by a single fuzzy subset. For Archimedean t-norms, decomposable indistinguishability operators generate special kinds of betweenness relations that characterize them. A new way to generate indistinguishability operators coherent with the underlying ordering structure of the real line is given in the sense that this structure is compatible with the betweenness relation generated by the relation is developed.
Learning user interests for a session-based personalized search
Authors: Mariam Daoud, Lynda Tamine-Lechani, Mohand Boughanem
Venue: Proceedings of the second international symposium on Information interaction in context (2008)

It is now widely assumed in personalized information retrieval (IR) area that user interests can provide substantial clues for document relevance estimation. User interests reflect generally the user background and topics of interests. However most of the proposed personalized retrieval models and strategies do not distinguish between short term and long term user interests and make use of the whole search history to improve the search accuracy. In this paper, we study how to learn long term user interests by aggregating concept-based short term ones identified within related search activities. For this purpose, we tackle the problem of session boundary recognition using context-sensitive similarity measures that are able to gauge the changes in the user interest topics with regard to reference ontology. Finally, the search personalization is achieved by re-ranking the search results for a given query using the short term user interest. Our experimental evaluation is carried out using TREC collection and shows that personalization brings significant improvements in retrieval effectiveness. Moreover, we observe that our context-sensitive session boundary recognition method can, to some extent, find a semantic correlation between the query and the user context across the search sessions.
Mobile Cultural Heritage: The Case Study of Locri
Authors: Giuseppe Cutrí, Giuseppe Naccarato, Eleonora Pantano
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

The goal of this project is to study the use of mobile technologies equipped with global positioning systems as an information aid for archaeological visits. In this study we will focus in the study of the technologies used to implement these systems. To this end we analyze an archaeological site where this systems have been tested. In this experiment we have applied state of the art technologies in virtual and augmented reality to implement a system that allows users to access the site using their mobile devices. We conclude that the use of this kind of technologies is an effective tool to promote the archeo-geographical value of the site.
Improving the Quality of Information for Software Project Management
Authors: Michael Berry, Chris S. Johnson
Venue: Software Process and Product Measurement: International Conference, IWSM-Mensura 2007, Palma de Mallorca, Spain, November 5-8, 2007. Revised Papers (2007)

Background. The goal of software measurement and analysis is to produce information for the people performing technical and managerial tasks. Information-centric assessment can identify opportunities to better meet that goal. This paper presents a study into the assessment of Information Quality for Software Project Management using generic and targeted information quality models. The setting for the study is a university software project management subject in which the students must complete a major exercise as part of the subject that attempts to replicate real-world project planning. Methods. After the exercise has been completed, the students are surveyed about the quality of the information with which they were supplied to complete the project planning exercise. The survey instrument is based on a generic model of information quality and a targeted model that focuses on the information for specific planning tasks. The study has been run with two cohorts of students and was run with a third cohort at the end of May 2007. Results. Improvement opportunities were identified through the 2006 assessment. These improvements were implemented for the third student cohort and the success of these improvements evaluated. The information quality assessment methods used in this study are likely to be of benefit to software project managers by providing the means to identify and remedy deficiencies in the information that they use to carry out their activities.
Learning and Forgetting with Local Information of New Objects
Authors: Fernando D. Vázquez, J. Salvador Sánchez, Filiberto Pla
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to incorporate new knowledge from the experience obtained when classifying new objects and correspondingly, to improve the efficiency of the system. We employ a stochastic rule for classifying and editing, along with a condensing algorithm based on local density to forget superfluous data (and control the sample size). The effectiveness of the algorithm is experimentally evaluated using a number of data sets taken from the UCI Machine Learning Database Repository.
The influence of organizational culture on the adoption of extreme programming
Authors: Cristiano Tolfo, Raul Sidnei Wazlawick
Venue: Journal of Systems and Software (2008)

The adoption of extreme programming (XP) method requires a very peculiar cultural context in software development companies. However, stakeholders do not always consider this matter and tend to stand to technical requirements of the method. Hence this paper aims at identifying aspects of organizational culture that may influence favorably or unfavorably the use of XP. In order to identify those aspects, this study analyzes dimensions of organizational culture under the perspective of practices and values of XP. This paper is based on the review of the literature of the area and empirical observations carried out with six software companies. This study does not intend to develop a tool for measurement of XP's compatibility with the organizational culture of each company. It intends to provide parameters (favorable and unfavorable aspects) for previous consideration of the convenience of XP implementation.
Toward accessible 3D virtual environments for the blind and visually impaired
Authors: Gareth R. White, Geraldine Fitzpatrick, Graham McAllister
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

3D virtual environments are increasingly used for education, business and recreation but are often inaccessible to users who are visually impaired, effectively creating a digital divide. Interviews with 8 visually impaired expert users were conducted to guide design proposals, and a review of current research into haptics and 3D sound for auditory displays is presented with suggestions for navigation and feedback techniques to address these accessibility issues. The diversity and volatility of the environment makes Second Life an unusually complex research object, suggesting the applicability of our work for the field of HCI and accessibility in 3D virtual environments.
Probabilistic Explanation Based Learning
Authors: Angelika Kimmig, Luc Raedt, Hannu Toivonen
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

Explanation based learning produces generalized explanations from examples. These explanations are typically built in a deductive manner and they aim to capture the essential characteristics of the examples.Probabilistic explanation based learning extends this idea to probabilistic logic representations, which have recently become popular within the field of statistical relational learning. The task is now to find the most likely explanation why one (or more) example(s) satisfy a given concept. These probabilistic and generalized explanations can then be used to discover similar examples and to reason by analogy. So, whereas traditional explanation based learning is typically used for speed-up learning, probabilistic explanation based learning is used for discovering new knowledge.Probabilistic explanation based learning has been implemented in a recently proposed probabilistic logic called ProbLog, and it has been applied to a challenging application in discovering relationships of interest in large biological networks.