ppxscal/embedding_network huggingface dataset:
Enhanced integration of Java to symbian OS using smart pointers
Authors: Raine Mäkeläinen, Cristiano Di Flora, Tommi Mikkonen
Venue: Proceedings of the 6th international workshop on Java technologies for real-time and embedded systems (2008)

Porting software from one environment to another can be eased with virtual machines. Then, the virtual machine hides the particularities of one system, and allows running of the same applications in a set of environments. Unfortunately, there are also restrictions related to this approach. In particular, when a program running inside the virtual machine wishes to access the hosting system for e.g. improved performance or service that is readily available in the hosting system but not in the virtual machine, several complications exist. In this paper, we introduce an improved fashion to integrate mobile Java to Symbian OS environment using so-called smart pointers to ease the above problems. Towards the end of the paper, we also provide an evaluation on our prototype implementation to validate the approach.
Perfect Simulation of Stochastic Automata Networks
Authors: Paulo Fernandes, Jean-Marc Vincent, Thais Webber
Venue: Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications (2008)

The solution of continuous and discrete-time Markovian models is still challenging mainly when we model large complex systems, for example, to obtain performance indexes of parallel and distributed systems. However, iterative numerical algorithms, even well-fitted to a multidimensional structured representation of Markov chains, still face the state space explosion problem. Discrete-event simulations can estimate the stationary distribution based on long run trajectories and are also alternative methods to estimate performance indexes of models. Perfect simulation algorithms directly build steady-state samples avoiding the warm-up period and the initial state bias of forward simulations. This paper introduces the concepts of backward coupling and the advantages of monotonicity properties and component-wise characteristics to simulate Stochastic Automata Networks (SAN). The main contribution is a novel technique to solve SAN descriptions originally unsolvable by iterative methods due to large state spaces. This method is extremely efficient when the state space is large and the model has dynamic monotonicity because it is possible to contract the reachable state space in a smaller set of maximal states. Component-wise characteristics also contribute to the state space reduction extracting extremal states of the model underlying chain. The efficiency of this technique applied to sample generation using perfect simulation is compared to the overall efficiency of using an iterative numerical method to predict performance indexes of SAN models.
JML Runtime Assertion Checking: Improved Error Reporting and Efficiency Using Strong Validity
Authors: Patrice Chalin, Frédéric Rioux
Venue: Proceedings of the 15th international symposium on Formal Methods (2008)

The Java Modeling Language (JML) recently switched to an assertion semantics based on "strong validity" in which an assertion is taken to be valid precisely when it is defined and true. Elsewhere we have shared our positive experiences with the realization and use of this new semantics in the context of ESC/Java2. In this paper, we describe the challenges faced by and the redesign required for the implementation of the new semantics in the JML Runtime Assertion Checker (RAC) compiler. Not only is the new semantics effective at helping developers identify formerly undetected errors in specifications, we also demonstrate how the realization of the new semantics is more efficient--resulting in more compact instrumented code that runs slightly faster. More importantly, under the new semantics, the JML RAC can now compile sizeable JML annotated Java programs (like ESC/Java2) which it was unable to compile before.
The Pricing Strategy Analysis for the "Software-as-a-Service" Business Model
Authors: Dan Ma, Abraham Seidmann
Venue: Proceedings of the 5th international workshop on Grid Economics and Business Models (2008)

The Software-as-a-Service (SaaS) model is a novel way of delivering software applications. In this paper, we present an analytical model to study the competition between the SaaS and the traditional COTS (Commercial off-the-shelf) software. The main research goal is to analyze the pricing strategy of the SaaS in a competitive setting. The model captures the most salient differences between the SaaS and COTS, including their distinct pricing structures, user initial setup costs, system customization levels, and delivery channels. We find that the two could coexist in a competitive market in the long run, and more importantly, we show how the SaaS could gradually take over the whole market even when its quality is inferior. Surprisingly, our analysis shows that the SaaS should raise (reduce) its prices when its software quality declines (increases) over time (in the relative sense).
Improving Imbalanced Multidimensional Dataset Learner Performance with Artificial Data Generation: Density-Based Class-Boost Algorithm
Authors: Ladan Malazizi, Daniel Neagu, Qasim Chaudhry
Venue: Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects (2008)

Improving the learner performance over imbalanced and multidimensional datasets raises a challenging task for machine learning community. Although a salient characteristic in data modeling is the amount of data provided for the learner, the proportional distribution of that data in each class has also direct relationship with the classifier performance. In imbalanced datasets when data is distributed into different classes, various in size, understanding of data structure and characteristics plays an important role in improving the learner accuracy. In this paper we introduce a new approach that combines the information gained from traditional classification algorithms, confusion matrix parameters and density-based clustering to generate artificial data in order to increase the learner performance. First a classification algorithm is run on training data. Then the confusion matrix is studied and the True Positive (TP) rate of each class is measured. The class with the lowest TP rate is selected. Using density-based clustering we identify the centroid of the class and measure the samples distribution in multidimensional space in the next step. With the values gained from Probability Density Function estimations for clusters, extra samples are generated and added to the original dataset to rebalance the class proportion and the weight of different classes in the whole training set. Our method has been evaluated in terms of TP, F-Measure and also overall accuracy against a number of Demetra (toxicology) and UCI datasets. Our method provides an insight view of the data structure and characteristics in order to identify how much and where the data need to be added for increasing the classification accuracy of the learner.
An Occupancy Grids Building Method with Sonar Sensors Based on Improved Neural Network Model
Authors: Hongshan Yu, Yaonan Wang, Jinzhu Peng
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper presents an improved neural network model interpretating sonar readings to build occupancy grids of mobile robot. The proposed model interprets sensor readings in the context of their space neighbors and relevant successive history readings simultaneously. Consequently the presented method can greatly weaken the effects by multiple reflections or specular reflection. The output of the neural network is the probability vector of three possible status(empty, occupancy, uncertainty) for the cell. As for sensor readings integration, three probabilities of cell's status are updated by the Bayesian update formula respectively, and the final status of cell is defined by Max-Min principle.Experiments performed in lab environment has shown occupancy map built by proposed approach is more consistent, accurate and robust than traditional method while it still could be conducted in real time.
Neural Network in Stable Adaptive Control Law for Automotive Engines
Authors: Shiwei Wang, Dingli Yu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper proposes to use a radial basis function (RBF) neural network in realising an adaptive control law for air/fuel ratio (AFR) regulation of automotive engines. The sliding mode control (SMC) structure is used and a new sliding surface is developed in the paper. The RBF network adaptation and the control law are derived using the Lyapunov method so that the entire system stability and the network convergence are guaranteed. The developed method is evaluated by computer simulation using the well-known mean value engine model (MVEM) and the effectiveness of the method is proved.
A Pattern Matching Algorithm in P2P Mobile QA System Answer Extracting Process
Authors: Lei Wang, Shulin Chen
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

Mobile automatic question and answer (QA) system ismore and more popular as a mobile value-addedbusiness. But the current mobile QA systems always havelow query precision and recall ratio. In this paper, a newalgorithm by pattern matching in p2p mobile QA systemanswer extracting process is designed. It expresses thedocument as triad and extracts the question and answersentence from the triad based documents. Simulationexperimental analysis results show that under idealconditions the system’s average responding time is lessthan 58ms and precision is above 66%, and the recallratio is upper than 52% when there are no more than3000 simultaneous query nodes, and so the completenessand feasibility of the system’s design is proved.
Optimizing unsupervised classifications of remotely sensed imagery with a data-assisted labeling approach
Authors: Ruili Lang, Guofan Shao, Bryan C. Pijanowski, Richard L. Farnsworth
Venue: Computers Geosciences (2008)

The quality of remotely sensed land use and land cover (LULC) maps is affected by the accuracy of image data classifications. Various efforts have been made in advancing supervised or unsupervised classification methods to increase the repeatability and accuracy of LULC mapping. This study incorporates a data-assisted labeling approach (DALA) into the unsupervised classification of remotely sensed imagery. The DALA-unsupervised classification algorithm consists of three steps: (1) creation of N spectral-class maps using Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA); (2) development of LULC maps with assistance of reference data; and (3) accuracy assessments of all the LULC maps using independent reference data and selection of one LULC map with the highest accuracy. Classification experiments with a composite image of a Landsat Thematic Mapper (TM) image and an Enhanced Thematic Mapper Plus (ETM+) image suggest that DALA was effective in making unsupervised classification process more objective, automatic, and accurate. A comparison between the DALA-unsupervised classifications and some conventional classifications suggests that the DALA-unsupervised classification algorithm yielded better classification accuracies compared to these conventional approaches. Such a simple, effective approach has not been systematically examined before but has great potential for many applications in the geosciences.
AISC Meets Natural Typography
Authors: James H. Davenport
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

McDermott [12,13] introduced the concept "Artificial Intelligence meets Natural Stupidity". In this paper, we explore how Artificial Intelligence and Symbolic Computation can meet Natural Typography, and how the conventions for expressing mathematics that humans understand can cause us difficulties when designing mechanised systems.
The 2004 European parliament election on the web: Finnish actor strategies and voter responses
Authors: Tom Carlson, Kim Strandberg
Venue: Information Polity (2005)

This article explores the internet's role in the Finnish 2004 European election. The first aim is to explore how different actors employed the web during the campaign. The second aim is to analyze the impact of the actors' web strategies on voters. Two circumstances make Finland interesting. First, the basic prerequisite for web campaigning is fulfilled since the northern countries, including Finland, are the most 'wired' area in Europe. Second, the electoral system is based on voters' direct choice of candidates, which encourages candidate-driven campaigning. The findings show that the main actors of Finnish campaigns, candidates and parties, dominated the on-line environment. Major party candidates, especially, campaigned on-line. Overall, the websites of all actors provided few information and engagement features. However, major party candidates made better use of the web than other candidates. Additionally, the news media's 'candidate selectors' made good use of web-specific features, and attracted relatively large voter interest. Concerning voter impact, few voters visited election-related websites. Moreover, few indicated that they obtained very/quite much information to support their voting decision from the web. Interestingly, young voters were an important exception.
Knowledge and Strategic Ability for Model Checking: A Refined Approach
Authors: Wojciech Jamroga
Venue: Proceedings of the 6th German conference on Multiagent System Technologies (2008)

We present a translation that reduces epistemic operators to strategic operators in the context of model checking. The translation is a refinement of the one from [4], and it improves on the previous scheme in two ways. First, it does not suffer any blowup in the length of formulae (the one from [4] did). Second, the new translation is defined in a more general setting: additional constraints can be imposed on strategy profiles that agents can execute. We show the applicability of such a general translation on the case of strategic abilities under imperfect information.
A review of the Bell Laboratories' digital computer developments
Authors: E. G. Andrews
Venue: Papers and discussions presented at the Dec. 10-12, 1951, joint AIEE-IRE computer conference: Review of electronic digital computers (1951)

The Bell Telephone Laboratories have designed and built seven digital computers. They are all electro-mechanical types using telephone systems relays and teletype transmitting and recording devices as their principal apparatus elements.
Quality of Feature Selection Based on Microarray Gene Expression Data
Authors: Henryk Maciejewski
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

This paper is devoted to the problem of feature selection for class prediction based on results of DNA microarray experiments. A method is presented to objectively compare quality of feature sets obtained using different gene-ranking methods. The quality of feature sets is expressed in terms of predictive performance of classification models built using these features. A comparative study is performed involving means comparison, fold difference and rank-test (Wilcoxon statistic) methods. The study shows that best performance can be obtained using the rank-test approach. It is also shown that the means comparison method can be significantly improved by also taking into account fold-change information. Performance of such mixed methods of feature selection can surpass performance of rank-test methods.
Data Flow Analysis of UML Action Semantics for Executable Models
Authors: Tabinda Waheed, Muhammad Zohaib Iqbal, Zafar I. Malik
Venue: Proceedings of the 4th European conference on Model Driven Architecture: Foundations and Applications (2008)

Executable modeling allows the models to be executed and treated as prototype to determine the behavior of a system. These models use precise action languages to specify the algorithms and computational details required for execution. These action languages are developed on the basis of UML action semantics metamodel that provides the abstract syntax. The use of a concrete action language makes a traditional model work like an executable one. The actions specified by the action language might involve variables and their data values that are useful to be analyzed in terms of data flow. In this paper, we provide data flow analysis (DFA) of the standard UML action semantics that can be used with executable models. The analysis provides a generic data flow at the abstract syntax level and allows a mapping to any of the action languages providing the concrete syntax. Our approach does not focus on a particular action language; therefore it can easily be applied to any concrete syntax. We apply the proposed approach to a case study and identify the data flow from executable UML state machine.
Toward Data Flow Oriented Services Composition
Authors: Nawal Guermouche, Claude Godart
Venue: Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference (2008)

Web service composition enables businesses to compile value-added services from elementary ones to build new complex services. Usually, Web service composition is needed when a client request cannot be fulfilled by one elementary service. In this paper, we propose a client data flow-tailored composition. The client request is defined by the sequences of data flow the client can provide and the sequences of data flow the client claims. Then, according to the client request, by defining the set of the available services, we aim at combining the services with the client request so that this later is satisfied.
Understanding the Technicalities of Photorealistic 3D Environments to Support Cinematography and Composition for Film and Animation
Authors: Jong Sze Joon, Soon Eu Hui, Yuen May Chan
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

This paper reviews the integration of Computer Graphics principles in simulating photorealistic 3D environments integrating life action footage for film. To achieve adequate believability and create impact, the look of the 3D background requires digital enhancement to achieve a certain stage of realism. This will depend primarily on the material/shader and renderer utilised in the 3D application. Despite having the realistic look, the other aspect to consider for a perfect merge between 3D and life requires one to skillfully match perspective and lighting. Another aspect to consider is the cinematography and composition of the scene.
AVSML: An XML-Based Markup Language for Web Information Integration in 3D Virtual Space
Authors: Yasuhiko Kitamura, Yatsuho Shibata, Keisuke Tokuda, Kazuki Kobayashi, Noriko Nagata
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

3D virtual space can visually represent the spatial structure to users and it has been applied to many fields such as city planning, navigation, education, entertainment and so on. In the 3D virtual space, an agent can navigate a user in an interactive manner [5]. Various platforms to build a 3D virtual space and languages to control the agents have been proposed [1,2,3,4]. For example, VKSC (Virtual Kobe Sanda Campus) is a 3D virtual space of Kobe Sanda Campus, Kwansei Gakuin University [1]. In VKSC, an agent called Suzie guides a user in the campus upon his/her request.
Algorithms for Computing the &lambda;-regularities in Strings
Authors: Hui Zhang, Qing Guo, Costas S. Iliopoulos
Venue: Fundamenta Informaticae (2008)

We introduce the notion of &lambda;-regularities in strings that consist of &lambda;-covers and &lambda;-seeds, and study three &lambda;-regularities problems - the &lambda;-cover problem, the general &lambda;-cover problem and the &lambda;-seed problem in this paper. &lambda;-regularities can be viewed as generalized string regularities in the sense that a set of &lambda; repetitive strings rather than a single repeated string are considered. We first present a general algorithm for computing all the &lambda;-combinations of a given string, since they serve as candidates for both &lambda;-covers and &lambda;-seeds. The running time of this algorithm is O(n$^2$). Relying on this result, we answer the above mentioned three problems all in O(n$^2$) time.
Semantic Service Discovery with QoS Measurement in Universal Network
Authors: Ying Zhang, Houkuan Huang, Youli Qu, Xiang Zhao
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

The service of Universal Network is different from that of current network, because the former has QoS (Quality of Service) grading. Therefore, service discovery of Universal Network is quite distinct from that of present network. In this paper, we present service discovery with QoS measurement to adapt to Universal Network. Many researches adopt semantic web technology-OWL-S (Web Ontology Language for Services), which is innovative for service discovery. With the aim of service discovery in Universal Network, we append QoS descriptions to OWL-S. Such OWL-S with QoS information is called OWL-QoS which is the groundwork for service discovery. Moreover, we also propose a matching algorithm that allows matching on the bases of capabilities and QoS descriptions of services.
A Novel Format-Compliant Video Encryption Scheme for H.264/AVC Stream Based on Residual Block Scrambling
Authors: Shu-Bo Liu, Zheng-Quan Xu, Wei Li, Jin Liu, Zhi-Yong Yuan
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

For secure stream media applications, block spatial scrambling can be used as a practice video encryption approach. The scrambling approaches commonly used for encryption of H.263/MPEG-4 stream can not be used for H.264/AVC's directly because the neighboring MacroBlocks, residual blocks and codewords of H.264/AVC stream data are context-sensitive. A novel format-compliant residual block spatial scrambling algorithm for H.264/AVC stream encryption is proposed in this article. In the algorithm, the residual blocks are categorized into different groups and each residual block group uses different random shuffling table, which is generated by the chaotic cryptosystem respectively. The experimental results show that H.264/AVC video stream could be encrypted in real-time while the format is kept compliant.
Cyber-vulnerability of power grid monitoring and control systems
Authors: Chee-Wooi Ten, Chen-Ching Liu, Manimaran Govindarasu
Venue: Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead (2008)

In this paper, a methodology is proposed for the evaluation of the impact of cyber attacks on the power grid. This is a systematical approach to evaluate the vulnerabilities of SCADA system at three levels, i.e., system, scenario, and access points. The impact of potential intrusion is evaluated based on the power flow solution. The cause-effect on the proposed method determines the likelihood of the consequence, which can be evaluated based on a substation outage. An IEEE 30 bus system is used to build a test case for the proposed method.