ppxscal/embedding_network huggingface dataset:
A Separation Bound for Real Algebraic Expressions
Authors: Christoph Burnikel, Stefan Funke, Kurt Mehlhorn, Stefan Schirra, Susanne Schmitt
Venue: Algorithmica (2009)

Real algebraic expressions are expressions whose leaves are integers and whose internal nodes are additions, subtractions, multiplications, divisions, k-th root operations for integral k, and taking roots of polynomials whose coefficients are given by the values of subexpressions. We consider the sign computation of real algebraic expressions, a task vital for the implementation of geometric algorithms. We prove a new separation bound for real algebraic expressions and compare it analytically and experimentally with previous bounds. The bound is used in the sign test of the number type leda::real.
RFID digital pheromones for generating stigmergic behaviour to autonomous mobile robots
Authors: I. Susnea, G. Vasiliu, A. Filipescu
Venue: Proceedings of the 4th WSEAS/IASME international conference on Dynamical systems and control (2008)

During the past years, the price of RFID tags have constantly dropped, while their technical performances increased. Along with the constant interest of the researchers for the problems of swarm intelligence, this opens a wide area of applications based on the use of RFID tags as storage media for digital pheromones, aimed to mediate the communication between various agents. A simple method to define digital pheromones as data structures and to simulate the evaporation process of the natural pheromones is described. This paper describes an experiment where RFID tags storing digital pheromones, deployed in an indoor environment, are used to define a dynamic path to be followed by autonomous mobile robots. The robots sense the pheoromones in the environment by means of a dual antenna, just like ants do, and a fuzzy controller governs the left-right movement thereof. The experimental results prove that the idea of using digital pheromones to control the movement of autonomous mobile robots is entirely feasible, even with very simple robots. This opens new possibilities to improve robot to robot and human to robot interaction. The idea of enabling mobile robots with new "senses", and thus going beyond the antropomorphic paradigm in robot control, seems to be productive.
Keywords in the mist: automated keyword extraction for very large documents and back of the book indexing
Authors: Rada F. Mihalcea
Venue:  (2008)

This research addresses the problem of automatic keyphrase extraction from large documents and back of the book indexing. The potential benefits of automating this process are far reaching, from improving information retrieval in digital libraries, to saving countless man-hours by helping professional indexers creating back of the book indexes.The dissertation introduces a new methodology to evaluate automated systems, which allows for a detailed, comparative analysis of several techniques for keyphrase extraction. We introduce and evaluate both supervised and unsupervised techniques, designed to balance the resource requirements of an automated system and the best achievable performance.Additionally, a number of novel features are proposed, including a statistical informativeness measure based on chi statistics; an encyclopedic feature that taps into the vast knowledge base of Wikipedia to establish the likelihood of a phrase referring to an informative concept; and a linguistic feature based on sophisticated semantic analysis of the text using current theories of discourse comprehension.The resulting keyphrase extraction system is shown to outperform the current state of the art in supervised keyphrase extraction by a large margin. Moreover, a fully automated back of the book indexing system based on the keyphrase extraction system was shown to lead to back of the book indexes closely resembling those created by human experts.
Personalized Web Service Ranking via User Group Combining Association Rule
Authors: Wenge Rong, Kecheng Liu, Lin Liang
Venue: Proceedings of the 2009 IEEE International Conference on Web Services (2009)

Web service plays an important role in implementing Service Oriented Architecture (SOA) for achieving dynamic business process. With the increased number of web services advertised in public repository, it is becoming vital to provide an efficient web service discovery and selection mechanism with respect to a user’s requirement. Considerable efforts have been made to solve this problem among which semantic based web service discovery has been attained much importance by researchers in academic and industry community. However, there is a challenge in the semantic based web service discovery process, that is, among the retrieved set of semantically equivalent web service candidates, how to discern which one is the best? In this paper, inspired by collaborative filtering idea, a web service ranking framework is proposed in which a set of users with similar interest will be firstly identified. Afterwards, association rules will be found out by analyzing all web service composition transactions related to that set of users. By combining user group and association rule mined from that group, a personalized web service ranking mechanism is achieved and the experiment shows the promising result.
The 4th IJCAR Automated Theorem Proving System Competition - CASC-J4
Authors: Geoff Sutcliffe
Venue: AI Communications (2009)

The CADE ATP System Competition (CASC) is an annual evaluation of fully automatic, first order Automated Theorem Proving (ATP) systems. CASC-J4 was the thirteenth competition in the CASC series. Twenty-six ATP systems and system variants competed in the various competition and demonstration divisions. An outline of the competition design, and a commentated summary of the results, are presented.
A case study of API redesign for improved usability
Authors: Jeffrey Stylos, Benjamin Graf, Daniela K. Busse, Carsten Ziegler, Ralf Ehret, Jan Karstens
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

As software grows more complex, software developers’ productivity is increasingly defined by their ability to effectively reuse code. Even APIs (application programming interfaces) and other code explicitly intended for reuse are often difficult and time consuming for developers to use. This paper describes the user-centered design and evaluation process we evolved in redesigning SAP’s BRFplus - a business rules engine, whose API was created for platform development, but which is now also increasingly being used by application developers - even though it was not initially designed with their specific needs in mind. Our API redesign attempts to take both the initial as well as the new emergent user requirements into account. A usability evaluation of our proposed changes to the API suggests that our user-centered design process was successful in helping to create an API that significantly improved users’ productivity and better matches the different users’ needs.
H∞ filtering of 2-D discrete state-delayed systems
Authors: Dan Peng, Xinping Guan
Venue: Multidimensional Systems and Signal Processing (2009)

In this paper, we deal with delay-independent and delay-dependent H ¿ filtering problems for a class of two-dimensional (2-D) discrete time-invariant systems with state delays. The 2-D systems are described by local state-space (LSS) Fornasini---Marchesini (FM) second model. First, delay-dependent bounded real lemma is proposed through introducing free weighting matrices. Then the delay-independent and delay-dependent H ¿ filtering designs are developed to assure the stability and H ¿ performance ¿ of filtering error systems via LMIs' feasibility. Furthermore, the minimum H ¿ norm bound ¿ can be obtained by solving linear convex optimization problems. Numerical examples demonstrate the effectiveness and advantages of our results.
Efficient integral equation algorithms and their application to rfid installation
Authors: Valdis V. Liepa, Dipak L. Sengupta
Venue:  (2008)

This research reduces the expense of solving multiscale frequency domain surface integral equation problems by application of an efficient hierarchical geometry description and an alternative approach to matrix conditioning. The cost of preparing a structure for simulation is minimized by multilevel retention of facet translation and rotation data. Overlapping sub-domain bases are then simultaneously applied via a new iterative procedure that ascertains the common sub-basis solution to the overdetermined system. This approach is highly convergent and provides accurate solutions without degradation to existing O (N) fast algorithms. New sheet impedance forms are introduced ensuring proper material representation. These methods are then applied in the optimization of low frequency Tire Pressure Monitoring Sensor placement on a metallic vehicle rim. Test methods required for accurate measurement of low frequency magnetic fields are discussed and measurements of an automobile wheel under like stimuli match simulated results.
Feature extraction method for land consolidation from high resolution imagery
Authors: Rui Guo, Daoliang Li
Venue: WSEAS Transactions on Information Science and Applications (2009)

Land consolidation is a tool for increasing the area of the arable land and improving the effectiveness of land cultivation. With the development of high resolution image, the progress of land consolidation project can be monitored by acquiring information from the image objectively. This paper presents a method to extract the wells and roads in land consolidation project from high resolution images. The well extraction method is based on the gray-level template matching algorithm. The road extraction method is based on mathematical morphology, which is a method for detecting image components that are useful for representation and description. The vector planning maps and high resolution images used to monitor the completion of land consolidation project are registered. The candidate areas are created using the functions of buffer and extraction by mask in GIS. The well template is selected manually from the image. The template is used to find the wells which match the template perfectly. In the road extraction section, Top-hat transform and gray dilation are used to filter the noise of the image. In this way the road feature in the image became wider and even more obvious to be recognized. Then image binarization and thinning algorithm are used to extract the one-pixel centerline of the road. At last, the thinning results are converted to the final vector detection results.
Plenary lecture 2: utilization of Fluctuationlessness theorem in the remainder term of taylor polynomials
Authors: N. A. Baykara
Venue: Proceedings of the 2nd WSEAS international conference on Multivariate analysis and its application in science and engineering (2009)

The Fluctuationlessness approximation is based on a theorem which was conjectured and proven by M. Demiralp. This theorem states that the matrix representation of an algebraic operator which multiplies its argument by a scalar univariate function, is identical to the image of the independent variable's matrix representation over the same space via the same basis set, under that univariate function, when the uctuation terms are ignored. The same principle applies to multivariable functions too. In the first part of these lecture basic concepts of the Fluctuationlessness theorem are given and based on this theorem approximations to functions of a single variable as well as to multivariable functions are made by using the Taylor expansion with the remainder term expressed in integral form. Results are compared with those obtained from the corresponding Taylor series expansion without the error term. In the second part of the lecture, after using the Fluctuationlessness concept for approximations to univariate and multivariate functions by using the Taylor expansion with the explicit remainder term this approximate expression is integrated and a new quadrature-like numerical integration method is obtained. The results of numerical experiments are compared with the results obtained from the corresponding Taylor series expansion without the remainder term and errors are analyzed.
Recovery of 3D Solar Magnetic Field Model Parameter Using Image Structure Matching
Authors: Jong Kwan Lee, G. Allen Gary
Venue: Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques (2009)

An approach to recover a 3D solar magnetic field model parameter using intensity images of the Sun's corona is introduced. The approach is a quantitative approach in which the 3D model parameter is determined via an image structure matching scheme. The image structure matching measures the positional divergence (i.e., pixel-by-pixel shortest Euclidean distance) between the real coronal loop structures in a 2D image to sets of modeled magnetic field structures to determine the best model parameter for a given region on the Sun. The approach's effectiveness is evaluated through experiments on synthetic images and a real image.
Learning first-order probabilistic models with combining rules
Authors: Sriraam Natarajan, Prasad Tadepalli, Thomas G. Dietterich, Alan Fern
Venue: Annals of Mathematics and Artificial Intelligence (2008)

Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models describe probabilistic influences between attributes of objects that are related to each other through known domain relationships. To keep these models succinct, each such influence is considered independent of others, which is called the assumption of "independence of causal influences" (ICI). In this paper, we describe a language that consists of quantified conditional influence statements and captures most relational probabilistic models based on directed graphs. The influences due to different statements are combined using a set of combining rules such as Noisy-OR. We motivate and introduce multi-level combining rules, where the lower level rules combine the influences due to different ground instances of the same statement, and the upper level rules combine the influences due to different statements. We present algorithms and empirical results for parameter learning in the presence of such combining rules. Specifically, we derive and implement algorithms based on gradient descent and expectation maximization for different combining rules and evaluate them on synthetic data and on a real-world task. The results demonstrate that the algorithms are able to learn both the conditional probability distributions of the influence statements and the parameters of the combining rules.
Optimisation-based proximity queries and penetration depth computation
Authors: Charbel Fares, Yskandar Hamam
Venue: Virtual Reality (2009)

The virtual reality (VR) was found to be a perfect technique that could be used as a training approach, since it shows many advantages despite its weakness. In the VR some major bottlenecks arises namely the proximity queries (PQ) and penetration depth computation. This paper shows a novel algorithm used to solve those problems. Problems of PQ are ubiquitous within many tasks in computer graphics, virtual environments, robotics, manufacturing, and mechanical design. Interactions in any virtual scene usually involve contact or close proximity between its objects. Determining which pairs of objects are in contact or at close proximity is a complex task in most of the virtual environments. The PQ is the shortest vector over which one object needs to be translated in order to bring the pair in contact.
Secure group communication in wireless mesh networks
Authors: Jing Dong, Kurt Erik Ackermann, Cristina Nita-Rotaru
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Wireless mesh networks (WMNs) have emerged as a promising technology that offers low-cost community wireless services. Security is critical for the deployment of these services. Previous work focused primarily on MAC and routing protocol security, while application-level security has received relatively little attention. In this paper we focus on providing data confidentiality for group communications in WMNs. We propose a new protocol framework, Secure Group Overlay Multicast (SeGrOM), that employs decentralized group membership, promotes localized communication, and exploits the wireless broadcast nature to achieve efficient and secure group communication. We analyze the performance and discuss the security properties of our protocols. We demonstrate through simulations that our protocols provide good performance and incur a significantly smaller overhead than a baseline centralized protocol optimized for WMNs.
Optimizing Virtual Learning Environments for Effective Educational Experiences
Authors: Ramon Anibal Iriarte Casco, Shigeru Nakayama, Satoshi Ono, Hidetoshi Miyakawa
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

This research project is aimed to provide guidelines for technical and didactical optimization of virtual learning environments, thus rendering a more functional introduction of these systems to support online teaching/learning experiences. The project has been structured in four stages comprising a diagnosis of technical platforms, the development/enhancement of tools in an open source technical platform, the production of specifications for the development of educationally sound e-learning platforms and the provision of guidelines for effective teaching/learning practice in virtual spaces. Findings and products from this work are expected to support a more extended and adequate use of Open Source Virtual Learning Environments (OSVLE) in educational settings at different levels.
Techniques and data structures for efficient information access and retrieval in distributed networks
Authors: Christopher Carothers, Konstantin Busch
Venue:  (2008)

Networks were designed and continue to exist to allow for fast and convenient access to remote data. With data scattered across a large network, there exists a fundamental challenge to efficiently find any sought data. This challenge is further complicated when the data is periodically relocated in the network, as is the case with wireless sensor networks. Thus, a solution to the problem necessitates a data structure with the ability to update in response to object relocations. A trivial solution to the problem uses a centralized directory responsible for knowing the location of all data at all times, and directing all querying nodes to the location of the data they seek. Dependence on one node to provide directions results in a single point of failure, and may cause some queries to be unnecessarily long, especially when the sought data lies at a node topologically close to the querying node. A better solution to the problem uses a distributed directory, where all queries are answered quickly regardless of the whereabouts of the querying and storing nodes. In this thesis, we provide significant improvements to previous distributed directory solutions by creating innovative algorithms that improve the structural properties of sparse covers, the underlying data structure from which a directory is built. Specifically, we improve directory performance to Stretch find = O(log n) and Stretchmove = O(log n) for H-minor free graphs (a savings of log n in each measure), and Stretchfind = O (1) and Stretchmove = O(log n) for planar graphs, unit disk graphs, and other graphs with a constant-stretch planar spanner (an additional savings of log n in Stretchfind).Once data is located in the network, it must then be retrieved (delivered). In a simple world, this delivery would be between a single source and a single destination. The possibilities for delivery techniques increase greatly when there are many sources and destinations, like in peer-to-peer (P2P) networks. P2P networks have gained much attention in recent years due to their scalability and fault-tolerance, and also their potential to drastically reduce distributor transit costs. In order to study the dynamics and causal relationships between peer entities in these complex overlay networks, we have developed a flow-based discrete-event simulator and abstract Internet topology model that accurately and realistically model today's broadband service, at a scale larger than previous efforts. Specifically, our model can scale to hundreds of thousands of peers, where prior efforts peak at only a few thousand. Using detailed simulations, we have improved the efficiency of data dissemination and reduced distributor transit costs for both the time-insensitive mass-download scenario and the real-time streaming scenario.
Advanced technology for E-learning development
Authors: Hazem M. El-Bakry, Nikos Mastorakis
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

Service Oriented Architecture (SOA) as a design pattern that presents systems as collection of reusable services that can be exposed and consumed on the Internet with standard interfaces has many advantages that can be achieved on technical, managerial, and implementation aspects of the system. Integrating University Management Information Systems (UMIS) and Learning Management Systems (LMS) can be achieved effectively, efficiently, and with minor modifications of both systems via SOA utilization. SOA can also be useful in integrating long decades and efforts of adaptive and intelligent features of E-Learning in today's information systems. Both UMIS and LMS; as the two major components of learning information systems can make use of adaptive and intelligent features became available over decades. Adaptive and intelligent features in information systems are many, and they can be utilized in new learning systems. Presenting adaptive and intelligent features as services with standard interfaces will allow different E-Learning systems to adopt them, so they will be reusable and newly introduced information systems will not have to redo the work again, besides, wrapping adaptive and intelligent features with standard interfaces will present a separation of interests that help adaptive and intelligent features' researchers and developers to focus more on their target and transfer the responsibility of utilizing those features in different information systems to information systems specialists. Today's E-Learning information systems' architects can make use of SOA in integrating major E-Learning components together, side by side with adaptive and intelligent features to provide students with personalized learning environment. This article reviews the E-Learning different models and the challenges facing E-Learning nowadays, supposing solution to those challenges. Reviewing the E-Learning proposed systems, architectures, and frameworks starting from traditional E-Learning systems through adaptive E-Learning systems supported by intelligent E-Learning features, methods, and techniques yields E-Learning researchers to Services based Adaptive and Intelligent E-Learning Systems.