ppxscal/embedding_network huggingface dataset:
Query Selectivity Estimation for Uncertain Data
Authors: Sarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil Prabhakar, Susanne Hambrusch
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

Applications requiring the handling of uncertain data have led to the development of database management systems extending the scope of relational databases to include uncertain (probabilistic) data as a native data type. New automatic query optimizations having the ability to estimate the cost of execution of a given query plan, as available in existing databases, need to be developed. For probabilistic data this involves providing selectivity estimations that can handle multiple values for each attribute and also new query types with threshold values. This paper presents novel selectivity estimation functions for uncertain data and shows how these functions can be integrated into PostgreSQL to achieve query optimization for probabilistic queries over uncertain data. The proposed methods are able to handle both attribute- and tuple-uncertainty. Our experimental results show that our algorithms are efficient and give good selectivity estimates with low space-time overhead.
Supporting Experience and Information Flow in Software Projects
Authors: Kurt Schneider
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

Several large companies have conducted initiatives for systematic learning from experience in software engineering. In the international Software Experience Center (SEC), for example, five companies exchanged experiences and collaborated in building experience exchange mechanisms to be used within each company. Many insights were gained and lessons were learned over the years, among them: (1) Written and documented experiences are the exception rather than the rule. (2) Although not documented in detail or controlled by a process, experience needs guidance and support in order to reach the designated person or group. The "flow" of experience must be kept in mind. (3) Experience is a delicate material, and any avoidable effort or threshold to participate in systematic experience exploitation may endanger stakeholder participation and success. (4) Tools can effectively be built to support orderly flow of experience, but they must be optimized for cognitive support of their users. These lessons learned from supporting experience exploitation can be applied to software projects more generally: Requirements, rationale, and other information flowing through a software project resemble experience with respect to the above-mentioned characteristics: They are often communicated orally rather than in a document. There are diverse processes and practices designed to channel information flow. Early and vague requirements must be handled with care, and tools need to be optimized to reduce cognitive barriers and thresholds, or they will not be accepted. A focus on information and experience flow takes the above-mentioned lessons into account. Information flows within one project, while experience often cuts across several projects. Requirements of one project are useful only in that same project. Experience in designing a product, however, may be reused in subsequent projects. Information and experience flows need to be modelled explicitly. A simple notation is proposed to capture just the essence of flowing information. What may seem like a subtle shift from processes to flows offers a new perspective: Based on those models, dedicated techniques and tools can be developed for analysing and for improving the flows. A wide range of current trends in software engineering can benefit from a better understanding of --- and support for --- appropriate information flow: Interfaces to the subcontractors, distributed and collaborative teams, Wiki webs, and a variety of new communication channels in global software engineering call for a focus on information flow. 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
Exploring the Solution Space of Sorting by Reversals, with Experiments and an Application to Evolution
Authors: Marília D. V. Braga, Marie-France Sagot, Celine Scornavacca, Eric Tannier
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

In comparative genomics, algorithms that sort permutations by reversals are often used to propose evolutionary scenarios of rearrangements between species. One of the main problems of such methods is that they give one solution while the number of optimal solutions is huge, with no criteria to discriminate among them. Bergeron et al. started to give some structure to the set of optimal solutions, in order to be able to deliver more presentable results than only one solution or a complete list of all solutions. However, no algorithm exists so far to compute this structure except through the enumeration of all solutions, which takes too much time even for small permutations. Bergeron et al. state as an open problem the design of such an algorithm. We propose in this paper an answer to this problem, that is, an algorithm which gives all the classes of solutions and counts the number of solutions in each class, with a better theoretical and practical complexity than the complete enumeration method. We give an example of how to reduce the number of classes obtained, using further constraints. Finally, we apply our algorithm to analyse the possible scenarios of rearrangement between mammalian sex chromosomes.
The eSTREAM Project
Authors: Matthew Robshaw
Venue: New Stream Cipher Designs: The eSTREAM Finalists (2008)

The origins of eSTREAM can be traced back to the 2004 RSA Data Security Conference. There, as part of the Cryptographer's Panel, Adi Shamir made some insightful comments on the state of stream ciphers. In particular, with AES [8] deployment being so wide-spread, Shamir wondered whether there remained a need for a stream cipher of dedicated design. As arguments against, one might observe that for most applications, the use of the AES in an appropriate stream cipher mode [9] frequently offers a perfectly adequate solution. Some also doubt our understanding of how best to design a dedicated stream cipher, a view somewhat supported by the lack of surviving stream ciphers in the NESSIE project [1]. However, as counter-arguments Shamir went on to identify two areas where a dedicated stream cipher might conceivably offer some advantage over block ciphers: (1) where exceptionally high throughput is required in software and (2) where exceptionally low resource consumption is required in hardware.
Experiments on the Multiple Linear Cryptanalysis of Reduced Round Serpent
Authors: Baydoin Collard, François-Xavier Standaert, Jean-Jacques Quisquater
Venue: Fast Software Encryption: 15th International Workshop, FSE 2008, Lausanne, Switzerland, February 10-13, 2008, Revised Selected Papers (2008)

In 2004, Biryukov et al. presented a new theoretical framework for the linear cryptanalysis of block ciphers using multiple approximations. Although they provided first experimental results to confirm the relevance of their approach, a scope for further research was to apply this framework to other ciphers. In this paper, we present various attacks against reduced-round versions of the AES candidate Serpent. Our results illustrate that the hypotheses of Crypto 2004 hold (at least) as long as the number of approximations exploited in the linear attack are computationally tractable. But they also underline the limits and specificities of Matsui's algorithms 1 and 2 for the exploitation of such approximations. In particular, they show that the optimal application of algorithm 2 requires good theoretical estimations of the approximation biases, which may be a problem when the linear hull effect is non-negligible. These results finally confirm the significant reductions of the attacks data complexity that can be obtained from multiple linear approximations.
An all closed set finding algorithm for data mining
Authors: Rein Kuusik, Grete Lind
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

In this paper we describe an algorithm named MONSA for closed sets mining. It is an exact depth-first search algorithm extracting only frequent closed sets using several pruning techniques to be free from repetitive and empty patterns. The first version of MONSA was created in 1993 and we have developed several versions during last years. Our algorithm does not use such kind of techniques as in ChARM by Zaki and Hsiao. In MONSA there is active only one branch which is under construction. All used techniques are proved. Our purpose is to introduce the approach used in MONSA and the correspondence of its basics and concepts to the approach by Zaki and Hsiao. We have used MONSA for creating a data mining method called Hypothesis Generator. By the algorithm the intersections (closed sets) and IF...THEN rules on the subsets of source data set simultaneously are found. MONSA does not depend on the initial order of objects. MONSA treats not only binary data, but a larger set of discrete values.
System Description: E- KRHyper
Authors: Björn Pelzer, Christoph Wernhard
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

The E-KRHyper system is a model generator and theorem prover for first-order logic with equality. It implements the new E-hyper tableau calculus, which integrates a superposition-based handling of equality into the hyper tableau calculus. E-KRHyper extends our previous KRHyper system, which has been used in a number of applications in the field of knowledge representation. In contrast to most first order theorem provers, it supports features important for such applications, for example queries with predicate extensions as answers, handling of large sets of uniformly structured input facts, arithmetic evaluation and stratified negation as failure. It is our goal to extend the range of application possibilities of KRHyper by adding equality reasoning.
Model Construction with External Constraints: An Interactive Journey from Semantics to Syntax
Authors: Mikoláš Janota, Victoria Kuzina, Andrzej Wąsowski
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

Mainstream development environments have recently assimilated guidance technologies based on constraint satisfaction. We investigate one class of such technologies, namely, interactive guided derivation of models, where the editing system assists a designer by providing hints about valid editing operations that maintain global correctness. We provide a semantics-based classification of such guidance systems and investigate concrete guidance algorithms for two kinds of modeling languages: a simple subset of class-diagram-like language and for feature models. Both algorithms are efficient and provide exhaustive guidance.
Learning Human Activity Containing Sparse Irrelevant Events in Long Sequence
Authors: Weidong Zhang, Feng Chen, Wenli Xu, Youtian Du
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In daily living, person often performs quite differently for finishing the same semantic task, because of her/his mood and the scene state of that time. A large amount of variations are caused by personal petty actions, aimless wandering and additive actions in special scenes, which we term irrelevant events. In this paper, we explore how activities containing sparse irrelevant events can be recognized. We introduce an irrelevant event state into hidden semi-Markov model to cover variations because of irrelevant events. The proposed model remains the partial order of sub-events of the activity of interest, and keeps its discriminability from others with the help of higher-order Markov setting. The experimental results demonstrate the efficiency of the proposed approach for human activity recognition.
Evaluating Quality Provisioning Levels in Service Oriented Business Environments
Authors: Konstantinos Tserpes, Dimosthenis Kyriazis, Andreas Menychtas, Antonios Litke, Costis Christogiannis, Theodora Varvarigou
Venue: Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference (2008)

This paper advocates the need for a mechanism that will allow the evaluation of the provided quality of service (QoS) by a service provider to a service customer in B2B service provisioning. Furthermore, this study goes on with presenting the feasibility of this mechanism by designing and testing a reference implementation that can be used in a Service Oriented Architecture (SOA) environment which is able to support business application services. Experience gained in the frame of the NextGRID IST project that focused on the business perspectives of Grid computing and adopted SOA as its baseline architecture, has shown that such a mechanism is essential for enabling the economic viability of such large scale computing platforms.
Transformation-Based Operationalization of Graph Languages
Authors: Erhard Weinell
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

Graph Languages emerged during the seventies from the necessity to process data structures with complex interrelations. Nowadays, various variants of these languages can be found for querying [1][2], in-place transforming [3][4], and translating graph structures [5][6]. Still, new graph languages supporting different paradigms and usage scenarios are proposed regularly. In fact, languages tailored for a dedicated application domain can be restricted to a concise and clear syntax representation, thus reducing effort to learn and apply them. Effectively aiding the development of graph languages, even though considering the already existing ones, therefore remains an important working topic.
Effect of Image Quality on Film Reading
Authors: Susan Astley, Neil Prasad, Eve Allcock, Jenny Diffey, Yit Yoong Lim, Caroline Boggis
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

Good image quality is essential for breast screening to ensure that low contrast and very small features are not misinterpreted or missed. Furthermore, results and performance standards using older screening films are often cited in more recent studies for comparative purposes. In this study we examine whether older films are of comparable standard to more recent ones in a film reading test, investigating density and difference of opinion between readers. We also compare the most recent results for screen-film screening with current digital reading performance.
Artificial intelligency methods used for electrical energy consumption forecasting
Authors: Petruta Mihai, Mihaela Matei, Claudia L. Popescu, Mihai O. Popescu
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

The aspects, presented in the paper, refer to an Artificial Neural Network (ANN) architecture for mid term, monthly load forecasting. The paper offers some recommendations for the training set used to teach the ANN, and also approaches an ANN learning method insuring quick load dynamics learning. The software created, based on these aspects, can analyze several load evolution scenarios and can establish a correct trend for the electric load evolution. Selection between different types of load forecasting are discussed in this paper.
Tailored Real-Time Simulation for Teams of Humanoid Robots
Authors: Martin Friedmann, Karen Petersen, Oskar Stryk
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

Developing and testing the key modules of autonomous humanoid robots (e.g., for vision, localization, and behavior control) in software-in-the-loop (SIL) experiments, requires real-time simulation of the main motion and sensing properties. These include humanoid robot kinematics and dynamics, the interaction with the environment, and sensor simulation. To deal with an increasing number of robots per team the simulation algorithms must be very efficient. In this paper, the simulator framework MuRoSimF (Multi-Robot-Simulation-Framework) is presented which allows the flexible and transparent integration of different simulation algorithms with the same robot model. These include several algorithms for simulation of humanoid robot motion kinematics and dynamics (with O(n) runtime complexity), collision handling, and camera simulation including lens distortion. A simulator for teams of humanoid robots based on MuRoSimF is presented. A unique feature of this simulator is the scalability of the level of detail and complexity which can be chosen individually for each simulated robot and tailored to the requirements of a specific SIL test. Performance measurements are given for real-time simulation on a moderate laptop computer of up to six humanoid robots with 21 degrees of freedom, each equipped with an articulated camera.
Hough transform neural network for pattern detection and seismic applications
Authors: Kou-Yuan Huang, Kai-Ju Chen, Jiun-Der You, An-Ching Tung
Venue: Neurocomputing (2008)

Hough transform neural network is adopted to detect the line pattern of direct wave and the hyperbolic pattern of reflection wave in a one-shot seismogram. We use time difference from point to hyperbola and line as the distance in the pattern detection of seismic direct and reflection waves. This distance calculation makes the parameter learning feasible. One set of parameters represents one pattern. Many sets of parameters represent many patterns. The neural network can calculate the distances from point to many patterns as total error. The parameter learning rule is derived by gradient descent method to minimize the total error. The network is applied to three kinds of data in the experiments. One is the line and hyperbolic pattern in the image data. The second is the simulated one-shot seismic data. And the last is the real one-shot seismic data. Experimental results show that lines and hyperbolas can be detected correctly in three kinds of data. The method can also tolerate certain level of noise data. The detection results in the one-shot seismogram can improve the seismic interpretation and further seismic data processing.
Election Security: Perception and Reality
Authors: David Evans, Nathanael Paul
Venue: IEEE Security and Privacy (2004)

Voters' trust in elections comes from a combination of the mechanisms and procedures we use to record and tally votes, and from confidence in election officials' competence and honesty. Electronic voting systems pose considerable risks to both the perception and reality of trustworthy elections.
Double Appraisal for Synthetic Characters
Authors: Sandy Louchart, Ruth Aylett, Joao Dias
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

The paper describes a double appraisal-based emotion system for synthetic characters. This approach gives intelligent agents the ability to make decisions with respect to the emotional states of others, thus implementing aspects of the theory of mind concept and laying the basis for cognitive empathy.
Information technology investment and the relationship to key hospital operational metrics: an exploratory analysis
Authors: Jose Nieves
Venue:  (2007)

The effect of computer technology on productivity and economic growth continues to be questioned by skeptics as being outright incorrect, a phenomenon known as the productivity paradox. The purpose of this quantitative study is to explore the ability to predict the power or impact that IT investment has on hospital operational metrics and to develop a linear regression model. The rationale for performing quantitative research is to develop a model to predict profitability changes, efficiency changes, or differed patient outcomes based upon IT investment. In evaluating the completed research findings, all null hypotheses were accepted. Though there was insufficient data to accept the alternative for any of the three hypotheses, there was compelling evidence that at least two should be explored further. Insight gathered from the research supports some correlation between IT investment to both hospital efficiency and profitability. The study has several implications and theoretical ramifications. Few studies address the topic and it would be beneficial for more research to contribute to exiting body of knowledge. In this respect the study was a success in spotlighting a research gap.
Use Semantic Decision Tables to Improve Meaning Evolution Support Systems
Authors: Yan Tang, Robert Meersman
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

Meaning Evolution Support Systems have been recently introduced as a real-time, scalable, community-based cooperative systems to support the ontology evolution. In this paper, we intend to address the problems of accuracy and effectiveness in Meaning Evolution Support Systems in general. We use Semantic Decision Tables to tackle these problems. A Semantic Decision Table separates general decision rules from the processes, bootstraps policies and template dependencies in the whole system. Recently, DOGMA-MESS ("Developing Ontology Grounded Methodology and Applications" framework based "Meaning Evolution Support Systems") is developed at VUB STARLab as a collection of meaning evolution support systems. We embed Semantic Decision Tables in DOGMA-MESS to illustrate our approach. Semantic Decision Tables play the roles in both top-down and bottom-up processes of the meaning evolution cycle. The decision rules that consist of templates dependency rules are mainly responsible for the top-down process execution. The bottom-up process execution relies on the ones that contain the concept lifting algorithms.
Compositional Abstraction in Real-Time Model Checking
Authors: Jasper Berendsen, Frits Vaandrager
Venue: Proceedings of the 6th international conference on Formal Modeling and Analysis of Timed Systems (2008)

The idea to use simulations (or refinements) as a compositional abstraction device is well-known, both in untimed and timed settings, and has already been studied theoretically and practically in many papers during the last three decades. Nevertheless, existing approaches do not handle two fundamental modeling concepts which, for instance, are frequently used in the popular Uppaal model checker: (1) a parallel composition operator that supports communication via shared variables as well as synchronization of actions, and (2) committed locations. We describe a framework for compositional abstraction based on simulation relations that does support both concepts, and that is suitable for Uppaal. Our approach is very general and the only essential restriction is that the guards of input transitions do not depend on external variables. We have applied our compositional framework to verify the Zeroconf protocol for an arbitrary number of hosts.
Virtual environment for solar energy systems design and testing
Authors: Lucian Milea, Orest Oltu, Marius Stoian, Sanda Osiceanu
Venue: Proceedings of the 6th WSEAS International Conference on Applied Electromagnetics, Wireless and Optical (2008)

This paper refers to a virtual environment which represents the main support for experiments with photovoltaic energy systems in the design and testing stage. This software environment is very useful because, compairing to the experiments with real energetic systems, it allow the testing and evaluation of different types of interfaces and different working environment conditions. A very important facility of this interactive software environment is the fact that the designers of the energetic systems sensors and interfaces are able to work in parallel to design test, optimize and realize different control devices for the energetic system.