ppxscal/embedding_network huggingface dataset:
Higher order mining
Authors: John F. Roddick, Myra Spiliopoulou, Daniel Lister, Aaron Ceglar
Venue: ACM SIGKDD Explorations Newsletter (2008)

The value of knowledge obtainable by analysing large quantities of data is widely acknowledged. However, so-called primary or raw data may not always be available for knowledge discovery for several reasons. First, cooperating institutions that are interested in sharing knowledge may not be willing (or allowed) to disclose their primary data. Second, data in the form of streams are only temporarily available for processing. If stored at all, stream data are maintained in the form of synopses or derived, abstract representations of the original data. Finally, even for non-stream data, there are limits on the computation speed to be achieved -- such limits are set by hardware and firmware technologies. This problem can only be partially solved through parallelization and increased processing power. Ultimately, in many cases data must be summarized to be processed efficiently. In the light of these observations, we anticipate the need for defining and practising data mining without the luxury of primary data. To that end, we formally introduce the paradigm of Higher Order Mining as a form of data mining that is applied over non-primary, derived data or patterns. Although Higher Order Mining is a new paradigm, there are already research advances on knowledge discovery methods from patterns rather than data. We discuss them and organize them under the light of the new paradigm. We show that the HOM paradigm reveals further potential for knowledge discovery, including the delivery of rules and patterns with semantics that are closer to human intuition and are thus more appropriate for human inspection.
Web-Based Environment for Active Computing Learners
Authors: Mohamed Hamada
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

Web-based learning is currently a hot research and development area. The benefits of web-based learning are clear at hand: learners can overcome the constraints of time, distance, and boundaries. On the other hand active learning provides a powerful mechanism to enhance depth of learning, increase material retention, and get learners involved with the material instead of passively participate in the learning process. In this paper, a research using Java2D as an example of web-based active learning tools in computing courses will be given. In addition, an evaluation of the tools in practice is given, which shows an improvement in the learners performance in classes.
A Comparison of Four Data Mining Models: Bayes, Neural Network, SVM and Decision Trees in Identifying Syndromes in Coronary Heart Disease
Authors: Jianxin Chen, Yanwei Xing, Guangcheng Xi, Jing Chen, Jianqiang Yi, Dongbin Zhao, Jie Wang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Coronary heart disease (CHD) is a serious disease causing more and more morbidity and mortality. Combining western medicine and Traditional Chinese Medicine (TCM) to heal CHD becomes especially necessary for medical society today. Since western medicine faces some problems, like high cost and more side effects. TCM can be a complementary alternative to overcome these defects. Identification of what syndrome a CHD patient caught has been a challenging issue for medical society because the core of TCM is syndrome. In this paper, we carry out a large-scale clinical epidemiology to collect data with 1069 cases, each of which must be a CHD instance but may be diagnosed as different syndromes. We take blood stasis syndrome (frequency is 69%) as an example, employ four distinct kinds of data mining algorithms: Bayesian model; Neural Network; Support vector machine and Decision trees to classify the data and compare their performance. The results indicated that neural network is the best identifier with 88.6% accuracy on the holdout samples. The next is support vector machine with 82.5% accuracy, a slight higher than Bayesian model with 82.0% counterpart. The decision tree performs the worst, only 80.4%. We conclude that in identifying syndromes in CHD, neural network can provide a best insight to clinical application.
PlanetSim: an extensible framework for overlay network and services simulations
Authors: Jordi Pujol Ahulló, Pedro García López
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

Research community on distributed systems, and in particular on peer-to-peer systems, needs tools for evaluating their own protocols and services, as well as against other protocols with the same precondictions. Since a (TCP/IP) experimental evaluation is not always feasible, simulation tools appeared. Nevertheless, the vast majority of them are ad-hoc customized simulators [3] and they are not for general overlay evaluation purposes, poorly documented or not extensible to other protocols and settings. Thus, in this paper we are mainly interested in extensible, scalable, high-level overlay and services simulation frameworks. In particular, we focus on structured (e.g. Chord, Pastry) and unstructured (e.g. Gnutella) peer-to-peer systems and services simulation onto our simulator PlanetSim.
Flexible Concurrency Control for Real-Time Collaborative Editors
Authors: Abdessamad Imine
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

Real-time Collaborative Editors (RCE) provide computer support for modifying simultaneously shared documents, such as articles, wiki pages and programming source code, by dispersed users. Due to data replication, Operational Transformation (OT) is considered as the efficient and safe method for consistency maintenance in the literature of collaborative editors. Indeed, it is aimed at ensuring copies convergence even though the users's updates are executed in any order on different copies. Unfortunately, existing OT algorithms often fail to achieve this objective. Moreover, these algorithms have limited scalability with the number of users as they use vector time stamps to enforce causality dependency. In this paper, we present a novel framework for managing collaborative editing work in a scalable and decentralized fashion. It may be deployed easily on P2P networks as it supports dynamic groups where users can leave and join at any time.
Architecture-Based Reasoning About Performability in Component-Based Systems
Authors: Heinz W. Schmidt
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

Scalable models of extra-functional properties such as reliability, availability and timeliness are still presenting great challenges to researchers and practitioners in component-based software architecture.In our research centre at Monash in collaboration with industrial partners and other universities, we have been developing compositional dynamic models for such extra-functional properties. Architecture definitions supported by our tool Radl cater for components that are parameterised by environment characteristics, such as configuration choices, deployment context or run-time usage profiles.The behaviour of such components is characterised by annotated automata and Petri nets. Annotations capture synchronisation and resource constraints, such as timing, as well as execution probabilities for run types.This paper provides a short survey of work around Radl over the past years and sheds light on some key aspects which have led to using Radl in industrial applications for the analysis of large-scale real-world component-based systems.
Convergence at prominent agents: a non-flat synchronization model of situated multi-agents
Authors: Jiuchuan Jiang, Yichuan Jiang
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

This paper presents a novel non-flat synchronization model where the synchronization capacity of each agent is different regarding its social rank and strategy dominance. In the presented model, the prominent agents may have higher synchronization forces, and finally the collective synchronization results may incline to converge at such prominent agents' strategics, which is called prominence convergence in collective synchronization and proved by our experimental results. The presented model can well match the peculiarities of real multi-agent societies where each agent plays a different role in the synchronization, and make up the restrictions of related benchmark works that only concerned about the flat synchronization.
AnySpot: Pervasive Document Access and Sharing
Authors: Jonathan Trevor, David M. Hilbert
Venue: IEEE Pervasive Computing (2007)

The Web, wireless devices, and wireless networks have increased the opportunities for supporting pervasive document access and sharing. However, today's solutions remain spotty in their coverage of pervasive information needs. To address this, the authors developed AnySpot, a Web-service-based platform for seamlessly connecting people to their personal and shared documents wherever they go. They describe AnySpot's design principles and how it meets users' key pervasive information needs. They also report on their experiences deploying it in a large, multi-national organization.
Pairing Lattices
Authors: Florian Hess
Venue: Proceedings of the 2nd international conference on Pairing-Based Cryptography (2008)

We provide a convenient mathematical framework that essentially encompasses all known pairing functions based on the Tate pairing and also applies to the Weil pairing. We prove non-degeneracy and bounds on the lowest possible degree of these pairing functions and show how endomorphisms can be used to achieve a further degree reduction.
A New Mutation Operator for the Elitism-Based Compact Genetic Algorithm
Authors: Rafael R. Silva, Heitor S. Lopes, Carlos R. Erig Lima
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

A Compact Genetic Algorithm (CGA) is a genetic algorithm specially devised to meet the tight restrictions of hardware-based implementations. We propose a new mutation operator for an elitism-based CGA. The performance of this algorithm, named emCGA, was tested using a set of algebraic functions for optimization. The optimal mutation rate found for high-dimensionality functions is around 0.5%, and the low the dimension of the problem, the less sensitive is emCGA to the mutation rate. The emCGA was compared with other two similar algorithms and demonstrated better tradeoff between quality of solutions and convergence speed. It also achieved such results with smaller population sizes than the other algorithms.
Ultrasound Estimation of Fetal Weight with Fuzzy Support Vector Regression
Authors: Jin-Hua Yu, Yuan-Yuan Wang, Ping Chen, Yue-Hua Song
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Accurate acquisition of expected fetal weight (EFW) based on ultrasound measurements is important to antenatal care. The accuracy of EFW is disturbed by random error of measurements and impropriety of regression method. There have been several studies using neural networks to improve estimation validity, but these methods are all on the premises of measurements accuracy. This paper utilizes the fuzzy logic to deal with the measurements inconsistence, while combines with the support vector regression (SVR) to pursue generalization ability. By this way, the suspect inaccurate measurements can have relatively less contributions to the learning of new fuzzy support vector regression (FSVR). Tests on a clinical database show that proposed algorithm can achieve 6.09% mean absolute percent error (MAPE) for testing group while the back-propagation algorithm and classical SVR achieve 8.95% and 7.23% MAPE respectively. Experimental results show the effectives of the proposed algorithm over traditional methods based on neural network.
Applying Genetic Programming to Civil Engineering in the Improvement of Models, Codes and Norms
Authors: Juan L. Pérez, Mónica Miguélez, Juan R. Rabuñal, Fernando Martínez Abella
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

This paper presents the use of Evolutionary Computation (EC) techniques, and more specifically the Genetic Programming (GP) technique, to Civil Engineering. This technique is applied here to a phenomenon that models the performance of structural concrete under controlled conditions throughout time. Several modifications were applied to the classic GP algorithm given the temporal nature of the case to be studied; one of these modifications was the incorporation of a new operator for providing the temporal ability for this specific case. The fitness function has been also modified by adding a security coefficient that adjusts the GP-obtained expressions and penalises the expressions that return unstable values.
Ambient Temperature Modelling through Traditional and Soft Computing Methods
Authors: Francesco Ceravolo, Matteo Felice, Stefano Pizzuti
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

This paper presents a new hybrid approach based both on traditional and soft computing techniques to provide ambient temperature for those places where such a datum is not available. Indeed, we combine neural networks with the nearest neighbouring algorithm; we use a fuzzy logic decision maker and later compare the results of each single technique to the hybrid one. Experiments have been performed on several Italian places; results have shown a remarkable improvement in accuracy compared to single methods.
Covering the Intangibles in a KM Initiative
Authors: James L. Poage
Venue: IT Professional (2003)

What if it works but no one will use it? Design your KM initiative to fit your organization's work habits, needs, and expectations. 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
Introduction to Part IV Assessment
Authors: Michael Kölling
Venue: Reflections on the Teaching of Programming: Methods and Implementations (2008)

The last section of this book is concerned with another difficult element of programming teaching at educational institutions, that of assessment.Assessing programming-related courses has always been difficult. The difficulties are caused by a wide variety of reasons because some are intrinsic to the subject and some are caused by aspects of the course.
Experiential Coe-Tutoring: A Report on Taiwan's OpenStudy Project That Seeks Innovative Accessible E-Learning Methodologies
Authors: Arrmien M. Chou, Yaoming Yeh, Shumei Keng, Chenchuan C. Chen, Tingyu Huang
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

This paper will report on the accessible OpenStudy e-learning project that aims to narrow the digital divide of people with disabilities in Taiwan. Not only does the project deploy accessible e-learning infrastructure and service, it also applies an innovative experiential coe-tutoring technique in order to fulfill the objectives and the challenges of multi-cultural and multi-scenario e-learning. We also describe the methodologies that we use, and some of the results.
Spatial Consistency in 3D Tract-Based Clustering Statistics
Authors: Matthan Caan, Lucas Vliet, Charles Majoie, Eline Aukema, Kees Grimbergen, Frans Vos
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We propose a novel technique for tract-based comparison of DTI-indices between groups, based on a representation that is estimated while matching fiber tracts. The method involves a non-rigid registration based on a joint clustering and matching approach, after which a 3D-atlas of cluster center points is used as a frame of reference for statistics. Patient and control FA-distributions are compared per cluster. Spatial consistency is taken to reflect a significant difference between groups. Accordingly, a non-parametric classification is performed to assess the continuity of pathology over larger tract regions. In a study to infant survivors treated for medulloblastoma with intravenous methotrexate and cranial radiotherapy, significant decreases in FA in major parts of the corpus callosum were found.
A study of educational functions of mobile learning
Authors: Hung-Jen Yang, Y. M. Chu, L. W. Wang, Jui-Chen Yu, Hsieh-Hua Yang
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

The purpose of this study was to identify the educational functions of mobile learning. Based upon deducing from the definition of learning and special functions of mobile learning, four learning abilities enabled by mobile technology and six functions of mobile technology were founded. The learning ability could be expanded by mobile technology are remembering, sensing, assessing, and responding. Those educational functions of mobile learning are 1). user centered, 2). individual settings, 3). mobile, 4). durable, 5). network/ communication, and 6). ubiquitous. These four abilities under those six functions together would contribute to the results of effective mobile learning. A conceptual model was also presented.
Estimating Flexibility Requirements in a Demand-Driven Lean/JIT Environment
Authors: Peter Nielsen, Kenn Steger-Jensen
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

Demand-driven JIT manufacturing is based on the assumption of a level stable demand rate. This is however not the reality experienced by most companies. To handle fluctuations from a level stable demand rate, the manufacturing system needs flexibility. This paper presents a method for using estimated multivariate density distributions of periodic demand rates to establish when flexibility is needed and how much. The method is applied to data from a JIT manufacture finding that the company in question had an unstable demand rate and needed a great deal of flexibility if a low delivery time should be guaranteed.
Progress Implementing US E-Government Programs
Authors: Staff
Venue: I-WAYS - The Journal of E-Government Policy and Regulation (2005)

The second-year anniversary of adoption of The e-Government Act is evaluated in this report. There are many accomplishments the Office of Budget and Management (OMB) reports, however, there are some shortcomings. Most of the provisions of the Act have been successfully implemented, but OMB has failed to develop a database and website containing information about all federally funded research and development. Because the US Government is probably the largest producer and user of information, its attention to achieving a high level of e-Government, including transactional services, is being closely observed by many countries. 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
Optimal Tableaux for Right Propositional Neighborhood Logic over Linear Orders
Authors: Davide Bresolin, Angelo Montanari, Pietro Sala, Guido Sciavicco
Venue: Proceedings of the 11th European conference on Logics in Artificial Intelligence (2008)

The study of interval temporal logics on linear orders is a meaningful research area in computer science and artificial intelligence. Unfortunately, even when restricted to propositional languages, most interval logics turn out to be undecidable. Decidability has been usually recovered by imposing severe syntactic and/or semantic restrictions. In the last years, tableau-based decision procedures have been obtained for logics of the temporal neighborhood and logics of the subinterval relation over specific classes of temporal structures. In this paper, we develop an optimal NEXPTIME tableau-based decision procedure for the future fragment of Propositional Neighborhood Logic over the whole class of linearly ordered domains.
Early Computer Developments in Madrid
Authors: Jose Garcia Santesmases
Venue: IEEE Annals of the History of Computing (1982)

Early computer developments and related topics at the University of Madrid and the Institute of Electricity and Automatics (CSIC) In Madrid (Spain) during the 1950s and 1960s are discussed. 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
Haptically-Aided Extrusion for Object Edition in CAD
Authors: Flavien Picon, Mehdi Ammi, Patrick Bourdot
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

CAD systems are powerful software tools used to manage numerical edition and simulation of products. Edition of CAD objects is a fundamental step in the lifecycle of these products. Although CAD benefits from improvements in functionalities, user interaction on these systems does not evolve anymore. Our goal is to propose novel haptic techniques to enhance user interaction with such applications. An important issue in CAD systems is the modification of the Boundary Representation (B-Rep) of 3D objects. Our general goal is to determine suitable haptic methods to increase accuracy of 3D interaction with CAD objects. This paper focuses on CAD edition processes based on parameterization of extrusion operators.
A Connectionist Architecture for Learning to Play a Simulated Brio Labyrinth Game
Authors: Larbi Abdenebaoui, Elsa A. Kirchner, Yohannes Kassahun, Frank Kirchner
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

The Brio labyrinth, is a popular game consisting of a board with holes and walls. In addition, the game has knobs which are used to tip the board in two planar directions for controlling the angle of the board. The aim of the game is to maneuver a steel ball along a marked path from a starting position to a final position on the board by tipping it so that the ball moves without falling into any of the holes. The path is partially bordered by the walls. Some of the walls form corners, where the ball can be controlled easily.
Texture classification using invariant ranklet features
Authors: Matteo Masotti, Renato Campanini
Venue: Pattern Recognition Letters (2008)

A novel invariant texture classification method is proposed. Invariance to linear/non-linear monotonic gray-scale transformations is achieved by submitting the image under study to the ranklet transform, an image processing technique relying on the analysis of the relative rank of pixels rather than on their gray-scale value. Some texture features are then extracted from the ranklet images resulting from the application at different resolutions and orientations of the ranklet transform to the image. Invariance to 90^o-rotations is achieved by averaging, for each resolution, correspondent vertical, horizontal, and diagonal texture features. Finally, a texture class membership is assigned to the texture feature vector by using a support vector machine (SVM) classifier. Compared to three recent methods found in literature and having being evaluated on the same Brodatz and Vistex datasets, the proposed method performs better. Also, invariance to linear/non-linear monotonic gray-scale transformations and 90^o-rotations are evidenced by training the SVM classifier on texture feature vectors formed from the original images, then testing it on texture feature vectors formed from contrast-enhanced, gamma-corrected, histogram-equalized, and 90^o-rotated images.